Updated on 2024/04/22

写真a

 
ODA, Masahiro
 
Organization
Information Technology Center Scholarly Information Division Associate professor
Graduate School
Graduate School of Informatics
Title
Associate professor
Contact information
メールアドレス
External link

Degree 1

  1. Doctor of Philosophy (Information Science) ( 2009.3   Nagoya University ) 

Research Interests 6

  1. Machine learning

  2. CAS

  3. CAD

  4. computer aided diagnosis

  5. computer assisted surgery

  6. Medical image processing

Research Areas 3

  1. Others / Others  / Medical Image Processing

  2. Others / Others  / Media Informatics/Database

  3. Life Science / Medical systems  / Medical Image Processing

Research History 6

  1. Nagoya University   Information Strategy Office, Information and Communications   Associate professor

    2020.10

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    Country:Japan

  2. Nagoya University   Department of Intelligent Systems, Graduate School of Informatics   Assistant Professor

    2017.4 - 2020.9

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  3. Nagoya University   Department of Media Science, Graduate School of Information Science   Assistant Professor

    2011.10 - 2017.3

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  4. Nagoya University   Strategy Office, Information and Communications Headquarters   Designated assistant professor

    2010.4 - 2011.9

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    Country:Japan

  5. Nagoya University   Innovative Research Center for Preventive Medical Engineering, Graduate School of Engineering   Designated assistant professor

    2009.8 - 2010.3

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    Country:Japan

  6. Nagoya University   Innovative Research Center for Preventive Medical Engineering, Graduate School of Engineering   Researcher

    2009.4 - 2009.7

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    Country:Japan

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Education 3

  1. Nagoya University   Division of Information Science, Graduate School of Information Science   Department of Media Science

    2006.4 - 2009.3

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    Country: Japan

  2. Nagoya University   Graduate School of Information Science   Department of Media Science

    2004.4 - 2006.3

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    Country: Japan

  3. Nagoya University   Faculty of Engineering   Department of Electrical and Electronic Engineering and Information Engineering

    2000.4 - 2004.3

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    Country: Japan

Professional Memberships 5

  1. The Institute of Electronics, Information and Communication Engineers

  2. Japan Society of Computer Aided Surgery

  3. The Japanese Society of Medical Image Technology

  4. Information Processing Society of Japan

  5. Japanese Society for Medical and Biological Engineering

Committee Memberships 40

  1. Medical Image Computing and Computer Assisted Intervention (MICCAI) 2024   Area Chair  

    2024.2 - 2024.10   

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    Committee type:Academic society

  2. JAMIT   Delegate  

    2022.4   

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    Committee type:Academic society

  3. The 41st JAMIT Annual Meeting (JAMIT 2022)   Chair of Program Committee  

    2022.2 - 2022.7   

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    Committee type:Academic society

  4. Medical Image Computing and Computer Assisted Intervention (MICCAI) 2025   Organization Committee  

    2022.1 - 2025.10   

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    Committee type:Academic society

  5. 日本コンピュータ外科学会   評議員  

    2017.4   

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    Committee type:Academic society

  6. CARS 2024 Computer Assisted Radiology and Surgery   Program Committee  

    2024.1 - 2024.6   

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    Committee type:Academic society

  7. The 42th JAMIT Annual Meeting   Program Committee  

    2023.4 - 2023.8   

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    Committee type:Academic society

  8. The 32nd Annual Congress of Japan Society of Computer Aided Surgery   Program Committee  

    2023.3 - 2023.12   

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    Committee type:Academic society

  9. The International Forum on Medical Imaging in Asia (IFMIA)   Program Committee  

    2022.7 - 2023.1   

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    Committee type:Academic society

  10. Editorial Committee of IEICE Transactions on Information and Systems   Member of Editorial Committee  

    2022.6 - 2026.6   

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    Committee type:Academic society

  11. 13th International Workshop on Machine Learning in Medical Imaging (MLMI2022)   Program Committee  

    2022.3 - 2022.9   

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    Committee type:Academic society

  12. The Japan Society of Computer Aided Surgery   Editorial Committee  

    2022.2 - 2023.11   

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    Committee type:Academic society

  13. The 31st Annual Congress of Japan Society of Computer Aided Surgery   Program Committee  

    2022.2 - 2022.6   

  14. The 30th Annual Congress of Japan Society of Computer Aided Surgery   Program Committee  

    2021.8 - 2021.11   

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    Committee type:Academic society

  15. The 40th JAMIT Annual Meeting   Program Committee  

    2021.5 - 2021.10   

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    Committee type:Academic society

  16. 12th International Workshop on Machine Learning in Medical Imaging (MLMI2021)   Program Committee  

    2021.3 - 2021.10   

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    Committee type:Academic society

  17. The 39th JAMIT Annual Meeting   Program Committee  

    2020.4 - 2020.9   

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    Committee type:Academic society

  18. 11th International Workshop on Machine Learning in Medical Imaging (MLMI2020)   Program Committee  

    2020.3 - 2020.10   

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    Committee type:Academic society

  19.   Local Arrangement Chair  

    2019.6 - 2020.1   

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    Committee type:Academic society

  20. The 38th JAMIT Annual Meeting   Program Committee  

    2019.4 - 2019.7   

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    Committee type:Academic society

  21. 10th International Workshop on Machine Learning in Medical Imaging (MLMI2019)   Program Committee  

    2019.3 - 2019.10   

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    Committee type:Academic society

  22.   Local Arrangement Chair  

    2018.6 - 2019.1   

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    Committee type:Academic society

  23. The 37th JAMIT Annual Meeting   Program Committee  

    2018.4 - 2018.7   

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    Committee type:Academic society

  24. 9th International Workshop on Machine Learning in Medical Imaging (MLMI2018)   Program Committee  

    2018.3 - 2018.9   

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    Committee type:Academic society

  25. 電子情報通信学会 医用画像研究専門委員会   専門委員  

    2017.6 - 2021.6   

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    Committee type:Academic society

  26.   Local Arrangement Chair  

    2017.6 - 2018.3   

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    Committee type:Academic society

  27. The 36th JAMIT Annual Meeting   Program Committee  

    2017.4 - 2017.7   

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    Committee type:Academic society

  28. The 26th Annual Congress of Japan Society of Computer Aided Surgery   Local Arrangement Chair  

    2016.10 - 2017.10   

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    Committee type:Academic society

  29. 日本医用画像工学会編集委員会   副編集委員長  

    2016.8 - 2020.7   

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    Committee type:Academic society

  30. 情報処理学会第79回全国大会   実行委員  

    2016.4 - 2017.3   

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    Committee type:Academic society

  31. The 35th JAMIT Annual Meeting   Program Committee  

    2016.4 - 2016.7   

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    Committee type:Academic society

  32.   Local Organizer  

    2016.1 - 2016.5   

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    Committee type:Academic society

  33. The 34th JAMIT Annual Meeting   Program Committee  

    2015.4 - 2015.8   

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    Committee type:Academic society

  34. 2nd International Workshop on Computer-Assisted and Robotic Endoscopy (CARE) 2015   Program Committee  

    2015.3 - 2015.10   

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    Committee type:Academic society

  35.   Member of editorial board  

    2014.8 - 2016.7   

  36. The 33rd JAMIT Annual Meeting   Program Committee  

    2014.4 - 2014.7   

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    Committee type:Academic society

  37. MICCAI 2013 5th International Workshop on Abdominal Imaging: Computational and Clinical Applications   Program Committee, Local Organizer  

    2013.4 - 2013.9   

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    Committee type:Academic society

  38. The 32nd JAMIT Annual Meeting   Program Committee  

    2013.4 - 2013.8   

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    Committee type:Academic society

  39. MICCAI 2013 steering committee   Executive Committee, Local Executive Committee, Local Arrangement Chair, Workshop Publicity Chair and Co-Chairs, Futsal Co-Chair  

    2012.5 - 2013.9   

  40. The 31st JAMIT Annual Meeting   Program Committee  

    2012.4 - 2012.8   

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    Committee type:Academic society

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Awards 11

  1. Endosopic Vision Challenge Sub Challenge 3rd Place

    2023.10   Endosopic Vision Challenge   Synthtic Date for Instrument segmentation in surgery

    Xinkai Zhao, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kensaku Mori

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    Award type:Award from international society, conference, symposium, etc.  Country:Canada

  2. Outstanding Paper Award

    2022.9   Joint MICCAI 2022 Workshop on Augmented Environments for Computer-Assisted Interventions (AE-CAI), Computer-Assisted Endoscopy (CARE), and Context-Aware Operation Theatres 2.0 (OR 2.0)   KST-Mixer: Kinematic Spatio-Temporal Data Mixer For Colon Shape Estimation

    Masahiro Oda, Kazuhiro Furukawa, Nassir Navab, Kensaku Mori

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    Award type:Award from international society, conference, symposium, etc.  Country:Singapore

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  3. Certificate of Merit

    2019.12   Radiological Society of North America   Generative Adversarial Networks Showcase: Their Mechanisms and Radiological Applications

    Masahiro Oda, Hirohisa Oda, Kanako K. Kumamaru, Shigeki Aoki, Hiroshi Natori, Kensaku Mori, Masaki Mori, Hirotsugu Takabatake

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    Award type:International academic award (Japan or overseas)  Country:United States

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  4. 2018年度 講演論文賞

    2019.11   日本コンピューター外科学会   医用画像処理のための深層学習サンプルコード集DMED

    小田昌宏, 原 武史, 森 健策

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  5. CAS Young Investigator Award Gold Award

    2018.11   Japan Society of Computer Aided Surgery  

    Masahiro Oda

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  6. 日本医用画像工学会 奨励賞

    2017.9   日本医用画像工学会  

    小田 昌宏, 山本 徳則, 吉野 能, 森 健策

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  7. Magna Cum Laude

    2014.12   The Radiological Society of North America  

    Kensaku Mori, Yoshihiko Nakamura, Yuichiro Hayashi, Masahiro Oda, Tsuyoshi Igami, Tomoaki Hirose

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    Award type:Award from international society, conference, symposium, etc.  Country:United States

  8. Certificate of Merit

    2009.12   The Radiological Society of North America  

    Masahiro Oda, Eichiro Fukano, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hiroshi Natori, Tetsuji Takayama, Hirotsugu Takabatake, Masaki Mori, Shigeru Nawano

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    Award type:Award from international society, conference, symposium, etc.  Country:United States

  9. 学生研究奨励賞

    2008.6   電子情報通信学会東海支部  

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  10. 電気関係学会東海支部連合大会 奨励賞

    2006.1   電子情報通信学会東海支部  

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    Country:Japan

  11. パターン認識・メディア理解(PRMU)研究会アルゴリズムコンテスト

    2002.9   パターン認識・メディア理解(PRMU)研究会  

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

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Papers 308

  1. Anatomical attention can help to segment the dilated pancreatic duct in abdominal CT.

    Shen C, Roth HR, Hayashi Y, Oda M, Sato G, Miyamoto T, Rueckert D, Mori K

    International journal of computer assisted radiology and surgery     2024.3

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    Language:English  

    DOI: 10.1007/s11548-023-03049-z

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  2. Use of 3D-printed model of liver by experts and novices Reviewed

    Akihiro Maehigashi, Kazuhisa Miwa, Masahiro Oda, Yoshihiko Nakamura, Kensaku Mori, Tsuyoshi Igami

    Current Psychology     2024.2

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    Publishing type:Research paper (scientific journal)  

    This study investigated the influence of using three-dimensional (3D) computer and 3D-printed models on the spatial reasoning of experts and novices. The task of this study required general university students as novices in Experiment 1 and surgeons specializing in digestive surgery as experts in Experiment 2 to infer the cross sections of a liver, using a 3D-computer or 3D-printed model. The results of the experiments showed that the university students learned faster and inferred the liver structure more accurately with the 3D-printed model than with the 3D-computer model. Conversely, the surgeons showed the same task performance when using the 3D-computer and 3D-printed models; however, they performed the task with more confidence and less workload during the task with the 3D-printed model. Based on the results, the cognitive effects and advantages of using 3D-printed models for novices and experts have been discussed.

    DOI: 10.1007/s12144-024-05676-4

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  3. YOLOv7-RepFPN: Improving real-time performance of laparoscopic tool detection on embedded systems Reviewed

    Yuzhang Liu, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kensaku Mori

    Healthcare Technology Letters     2024.1

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    Publishing type:Research paper (scientific journal)  

    This study focuses on enhancing the inference speed of laparoscopic tool detection on embedded devices. Laparoscopy, a minimally invasive surgery technique, markedly reduces patient recovery times and postoperative complications. Real-time laparoscopic tool detection helps assisting laparoscopy by providing information for surgical navigation, and its implementation on embedded devices is gaining interest due to the portability, network independence and scalability of the devices. However, embedded devices often face computation resource limitations, potentially hindering inference speed. To mitigate this concern, the work introduces a two-fold modification to the YOLOv7 model: the feature channels and integrate RepBlock is halved, yielding the YOLOv7-RepFPN model. This configuration leads to a significant reduction in computational complexity. Additionally, the focal EIoU (efficient intersection of union) loss function is employed for bounding box regression. Experimental results on an embedded device demonstrate that for frame-by-frame laparoscopic tool detection, the proposed YOLOv7-RepFPN achieved an mAP of 88.2% (with IoU set to 0.5) on a custom dataset based on EndoVis17, and an inference speed of 62.9 FPS. Contrasting with the original YOLOv7, which garnered an 89.3% mAP and 41.8 FPS under identical conditions, the methodology enhances the speed by 21.1 FPS while maintaining detection accuracy. This emphasizes the effectiveness of the work.

    DOI: 10.1049/htl2.12072

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  4. Deep learning model for extensive smartphone-based diagnosis and triage of cataracts and multiple corneal diseases.

    Ueno Y, Oda M, Yamaguchi T, Fukuoka H, Nejima R, Kitaguchi Y, Miyake M, Akiyama M, Miyata K, Kashiwagi K, Maeda N, Shimazaki J, Noma H, Mori K, Oshika T

    The British journal of ophthalmology     2024.1

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    DOI: 10.1136/bjo-2023-324488

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  5. Towards better laparoscopic video segmentation: A class-wise contrastive learning approach with multi-scale feature extraction

    Zhang L., Hayashi Y., Oda M., Mori K.

    Healthcare Technology Letters     2024

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    The task of segmentation is integral to computer-aided surgery systems. Given the privacy concerns associated with medical data, collecting a large amount of annotated data for training is challenging. Unsupervised learning techniques, such as contrastive learning, have shown powerful capabilities in learning image-level representations from unlabelled data. This study leverages classification labels to enhance the accuracy of the segmentation model trained on limited annotated data. The method uses a multi-scale projection head to extract image features at various scales. The partitioning method for positive sample pairs is then improved to perform contrastive learning on the extracted features at each scale to effectively represent the differences between positive and negative samples in contrastive learning. Furthermore, the model is trained simultaneously with both segmentation labels and classification labels. This enables the model to extract features more effectively from each segmentation target class and further accelerates the convergence speed. The method was validated using the publicly available CholecSeg8k dataset for comprehensive abdominal cavity surgical segmentation. Compared to select existing methods, the proposed approach significantly enhances segmentation performance, even with a small labelled subset (1–10%) of the dataset, showcasing a superior intersection over union (IoU) score.

    DOI: 10.1049/htl2.12069

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  6. M U-Net: Intestine Segmentation Using Multi-dimensional Features for Ileus Diagnosis Assistance

    An Q., Oda H., Hayashi Y., Kitasaka T., Hinoki A., Uchida H., Suzuki K., Takimoto A., Oda M., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 14313 LNCS   page: 135 - 144   2024

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    Publisher:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    The intestine is an essential digestive organ that can cause serious health problems once diseased. This paper proposes a method for intestine segmentation to intestine obstruction diagnosis assistance called multi-dimensional U-Net (M U-Net). We employ two encoders to extract features from two-dimensional (2D) CT slices and three-dimensional (3D) CT patches. These two encoders collaborate to enhance the segmentation accuracy of the model. Additionally, we incorporate deep supervision with the M U-Net to reduce the limitation of training with sparse label data sets. The experimental results demonstrated that the Dice of the proposed method was 73.22%, the recall was 79.89%, and the precision was 70.61%.

    DOI: 10.1007/978-3-031-47076-9_14

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  7. Revisiting instrument segmentation: Learning from decentralized surgical sequences with various imperfect annotations

    Zheng Z., Hayashi Y., Oda M., Kitasaka T., Mori K.

    Healthcare Technology Letters     2024

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    This paper focuses on a new and challenging problem related to instrument segmentation. This paper aims to learn a generalizable model from distributed datasets with various imperfect annotations. Collecting a large-scale dataset for centralized learning is usually impeded due to data silos and privacy issues. Besides, local clients, such as hospitals or medical institutes, may hold datasets with diverse and imperfect annotations. These datasets can include scarce annotations (many samples are unlabelled), noisy labels prone to errors, and scribble annotations with less precision. Federated learning (FL) has emerged as an attractive paradigm for developing global models with these locally distributed datasets. However, its potential in instrument segmentation has yet to be fully investigated. Moreover, the problem of learning from various imperfect annotations in an FL setup is rarely studied, even though it presents a more practical and beneficial scenario. This work rethinks instrument segmentation in such a setting and propose a practical FL framework for this issue. Notably, this approach surpassed centralized learning under various imperfect annotation settings. This method established a foundational benchmark, and future work can build upon it by considering each client owning various annotations and aligning closer with real-world complexities.

    DOI: 10.1049/htl2.12068

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  8. SGSR: style-subnets-assisted generative latent bank for large-factor super-resolution with registered medical image dataset. International journal

    Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Masahiro Oda, Kensaku Mori

    International journal of computer assisted radiology and surgery     2023.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    PURPOSE: We propose a large-factor super-resolution (SR) method for performing SR on registered medical image datasets. Conventional SR approaches use low-resolution (LR) and high-resolution (HR) image pairs to train a deep convolutional neural network (DCN). However, LR-HR images in medical imaging are commonly acquired from different imaging devices, and acquiring LR-HR image pairs needs registration. Registered LR-HR images have registration errors inevitably. Using LR-HR images with registration error for training an SR DCN causes collapsed SR results. To address these challenges, we introduce a novel SR approach designed specifically for registered LR-HR medical images. METHODS: We propose style-subnets-assisted generative latent bank for large-factor super-resolution (SGSR) trained with registered medical image datasets. Pre-trained generative models named generative latent bank (GLB), which stores rich image priors, can be applied in SR to generate realistic and faithful images. We improve GLB by newly introducing style-subnets-assisted GLB (S-GLB). We also propose a novel inter-uncertainty loss to boost our method's performance. Introducing more spatial information by inputting adjacent slices further improved the results. RESULTS: SGSR outperforms state-of-the-art (SOTA) supervised SR methods qualitatively and quantitatively on multiple datasets. SGSR achieved higher reconstruction accuracy than recently supervised baselines by increasing peak signal-to-noise ratio from 32.628 to 34.206 dB. CONCLUSION: SGSR performs large-factor SR while given a registered LR-HR medical image dataset with registration error for training. SGSR's results have both realistic textures and accurate anatomical structures due to favorable quantitative and qualitative results. Experiments on multiple datasets demonstrated SGSR's superiority over other SOTA methods. SR medical images generated by SGSR are expected to improve the accuracy of pre-surgery diagnosis and reduce patient burden.

    DOI: 10.1007/s11548-023-03037-3

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  9. Automated Detection of the Thoracic Ossification of the Posterior Longitudinal Ligament Using Deep Learning and Plain Radiographs

    Ito, S; Nakashima, H; Segi, N; Ouchida, J; Oda, M; Yamauchi, I; Oishi, R; Miyairi, Y; Mori, K; Imagama, S

    BIOMED RESEARCH INTERNATIONAL   Vol. 2023   page: 8495937   2023.11

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    Language:English   Publisher:BioMed Research International  

    Ossification of the ligaments progresses slowly in the initial stages, and most patients are unaware of the disease until obvious myelopathy symptoms appear. Consequently, treatment and clinical outcomes are not satisfactory. This study is aimed at developing an automated system for the detection of the thoracic ossification of the posterior longitudinal ligament (OPLL) using deep learning and plain radiography. We retrospectively reviewed the data of 146 patients with thoracic OPLL and 150 control cases without thoracic OPLL. Plain lateral thoracic radiographs were used for object detection, training, and validation. Thereafter, an object detection system was developed, and its accuracy was calculated. The performance of the proposed system was compared with that of two spine surgeons. The accuracy of the proposed object detection model based on plain lateral thoracic radiographs was 83.4%, whereas the accuracies of spine surgeons 1 and 2 were 80.4% and 77.4%, respectively. Our findings indicate that our automated system, which uses a deep learning-based method based on plain radiographs, can accurately detect thoracic OPLL. This system has the potential to improve the diagnostic accuracy of thoracic OPLL.

    DOI: 10.1155/2023/8495937

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  10. Automated Detection and Diagnosis of Spinal Schwannomas and Meningiomas Using Deep Learning and Magnetic Resonance Imaging

    Ito Sadayuki, Nakashima Hiroaki, Segi Naoki, Ouchida Jun, Oda Masahiro, Yamauchi Ippei, Oishi Ryotaro, Miyairi Yuichi, Mori Kensaku, Imagama Shiro

    JOURNAL OF CLINICAL MEDICINE   Vol. 12 ( 15 )   2023.8

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    Language:English   Publisher:Journal of Clinical Medicine  

    Spinal cord tumors are infrequently identified spinal diseases that are often difficult to diagnose even with magnetic resonance imaging (MRI) findings. To minimize the probability of overlooking these tumors and improve diagnostic accuracy, an automatic diagnostic system is needed. We aimed to develop an automated system for detecting and diagnosing spinal schwannomas and meningiomas based on deep learning using You Only Look Once (YOLO) version 4 and MRI. In this retrospective diagnostic accuracy study, the data of 50 patients with spinal schwannomas, 45 patients with meningiomas, and 100 control cases were reviewed, respectively. Sagittal T1-weighted (T1W) and T2-weighted (T2W) images were used for object detection, classification, training, and validation. The object detection and diagnosis system was developed using YOLO version 4. The accuracies of the proposed object detections based on T1W, T2W, and T1W + T2W images were 84.8%, 90.3%, and 93.8%, respectively. The accuracies of the object detection for two spine surgeons were 88.9% and 90.1%, respectively. The accuracies of the proposed diagnoses based on T1W, T2W, and T1W + T2W images were 76.4%, 83.3%, and 84.1%, respectively. The accuracies of the diagnosis for two spine surgeons were 77.4% and 76.1%, respectively. We demonstrated an accurate, automated detection and diagnosis of spinal schwannomas and meningiomas using the developed deep learning-based method based on MRI. This system could be valuable in supporting radiological diagnosis of spinal schwannomas and meningioma, with a potential of reducing the radiologist’s overall workload.

    DOI: 10.3390/jcm12155075

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  11. Artificial intelligence in a prediction model for postendoscopic retrograde cholangiopancreatography pancreatitis

    Takahashi Hidekazu, Ohno Eizaburo, Furukawa Taiki, Yamao Kentaro, Ishikawa Takuya, Mizutani Yasuyuki, Iida Tadashi, Shiratori Yoshimune, Oyama Shintaro, Koyama Junji, Mori Kensaku, Hayashi Yuichiro, Oda Masahiro, Suzuki Takahisa, Kawashima Hiroki

    DIGESTIVE ENDOSCOPY     2023.7

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    Language:English   Publisher:Digestive Endoscopy  

    Objectives: In this study we aimed to develop an artificial intelligence-based model for predicting postendoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP). Methods: We retrospectively reviewed ERCP patients at Nagoya University Hospital (NUH) and Toyota Memorial Hospital (TMH). We constructed two prediction models, a random forest (RF), one of the machine-learning algorithms, and a logistic regression (LR) model. First, we selected features of each model from 40 possible features. Then the models were trained and validated using three fold cross-validation in the NUH cohort and tested in the TMH cohort. The area under the receiver operating characteristic curve (AUROC) was used to assess model performance. Finally, using the output parameters of the RF model, we classified the patients into low-, medium-, and high-risk groups. Results: A total of 615 patients at NUH and 544 patients at TMH were enrolled. Ten features were selected for the RF model, including albumin, creatinine, biliary tract cancer, pancreatic cancer, bile duct stone, total procedure time, pancreatic duct injection, pancreatic guidewire-assisted technique without a pancreatic stent, intraductal ultrasonography, and bile duct biopsy. In the three fold cross-validation, the RF model showed better predictive ability than the LR model (AUROC 0.821 vs. 0.660). In the test, the RF model also showed better performance (AUROC 0.770 vs. 0.663, P = 0.002). Based on the RF model, we classified the patients according to the incidence of PEP (2.9%, 10.0%, and 23.9%). Conclusion: We developed an RF model. Machine-learning algorithms could be powerful tools to develop accurate prediction models.

    DOI: 10.1111/den.14622

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  12. DEVELOPMENT OF A MACHINE-LEARNING MODEL FOR PREDICTING POST-ERCP PANCREATITIS

    Takahashi Hidekazu, Eizaburo Ohno, Taiki Furukawa, Kentaro Yamao, Takuya Ishikawa, Yasuyuki Mizutani, Tadashi Iida, Yoshimune Shiratori, Shintaro Oyama, Junji Koyama, Kensaku Mori, Yuichiro Hayashi, Masahiro Oda, Takahisa Suzuki, Hiroki Kawashima

    Gastrointestinal Endoscopy   Vol. 97 ( 6 ) page: AB656 - AB656   2023.6

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    Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.gie.2023.04.1087

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  13. Gaussian affinity and GIoU-based loss for perforation detection and localization from colonoscopy videos

    Jiang Kai, Itoh Hayato, Oda Masahiro, Okumura Taishi, Mori Yuichi, Misawa Masashi, Hayashi Takemasa, Kudo Shin-Ei, Mori Kensaku

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 18 ( 5 ) page: 795 - 805   2023.5

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    Language:English   Publisher:International Journal of Computer Assisted Radiology and Surgery  

    Purpose: Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer. However, perforations may happen and cause peritonitis during ESD. Thus, there is a potential demand for a computer-aided diagnosis system to support physicians in ESD. This paper presents a method to detect and localize perforations from colonoscopy videos to avoid perforation ignoring or enlarging by ESD physicians. Method: We proposed a training method for YOLOv3 by using GIoU and Gaussian affinity losses for perforation detection and localization in colonoscopic images. In this method, the object functional contains the generalized intersection over Union loss and Gaussian affinity loss. We propose a training method for the architecture of YOLOv3 with the presented loss functional to detect and localize perforations precisely. Results: To qualitatively and quantitatively evaluate the presented method, we created a dataset from 49 ESD videos. The results of the presented method on our dataset revealed a state-of-the-art performance of perforation detection and localization, which achieved 0.881 accuracy, 0.869 AUC, and 0.879 mean average precision. Furthermore, the presented method is able to detect a newly appeared perforation in 0.1 s. Conclusions: The experimental results demonstrated that YOLOv3 trained by the presented loss functional were very effective in perforation detection and localization. The presented method can quickly and precisely remind physicians of perforation happening in ESD. We believe a future CAD system can be constructed for clinical applications with the proposed method.

    DOI: 10.1007/s11548-022-02821-x

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  14. Correction to: Gaussian affinity and GIoU-based loss for perforation detection and localization from colonoscopy videos.

    Jiang K, Itoh H, Oda M, Okumura T, Mori Y, Misawa M, Hayashi T, Kudo SE, Mori K

    International journal of computer assisted radiology and surgery   Vol. 18 ( 5 ) page: 807   2023.5

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    The original version of this article unfortunately contained a mistake. The incorrect notations were given in the author’s affiliations.

    DOI: 10.1007/s11548-023-02899-x

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  15. Deep learning-based prediction model for postoperative complications of cervical posterior longitudinal ligament ossification. Reviewed

    Ito S, Nakashima H, Yoshii T, Egawa S, Sakai K, Kusano K, Tsutui S, Hirai T, Matsukura Y, Wada K, Katsumi K, Koda M, Kimura A, Furuya T, Maki S, Nagoshi N, Nishida N, Nagamoto Y, Oshima Y, Ando K, Takahata M, Mori K, Nakajima H, Murata K, Miyagi M, Kaito T, Yamada K, Banno T, Kato S, Ohba T, Inami S, Fujibayashi S, Katoh H, Kanno H, Oda M, Mori K, Taneichi H, Kawaguchi Y, Takeshita K, Matsumoto M, Yamazaki M, Okawa A, Imagama S

    European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society     2023.2

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    DOI: 10.1007/s00586-023-07562-2

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  16. A semantic segmentation method for laparoscopic images using semantically similar groups

    Uramoto L., Hayashi Y., Oda M., Kitasaka T., Misawa K., Mori K.

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE   Vol. 12466   2023

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    In this paper, we present a segmentation method for laparoscopic images using semantically similar groups for multi-class semantic segmentation. Accurate semantic segmentation is a key problem for computer assisted surgeries. Common segmentation models do not explicitly learn similarities between classes. We propose a model that, in addition to learning to segment an image into classes, also learns to segment it into human-defined semantically similar groups. We modify the LinkNet34 architecture by adding a second decoder with an auxiliary task of segmenting the image into these groups. The feature maps of the second decoder are merged into the final decoder. We validate our method against our base model LinkNet34 and a larger LinkNet50. We find that our proposed modification increased the performance both with mean Dice (average +1.5%) and mean Intersection over Union metrics (average +2.8%) on two laparoscopic datasets.

    DOI: 10.1117/12.2654636

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  17. Improved method for COVID-19 Classification of Complex-Architecture CNN from Chest CT volumes using Orthogonal Ensemble Networks

    Toda R., Oda M., Hayashi Y., Otake Y., Hashimoto M., Akashi T., Aoki S., Mori K.

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE   Vol. 12465   2023

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    This paper introduces the improved method for the COVID-19 classification based on computed tomography (CT) volumes using a combination of a complex-architecture convolutional neural network (CNN) and orthogonal ensemble networks (OEN). The novel coronavirus disease reported in 2019 (COVID-19) is still spreading worldwide. Early and accurate diagnosis of COVID-19 is required in such a situation, and the CT scan is an essential examination. Various computer-aided diagnosis (CAD) methods have been developed to assist and accelerate doctors' diagnoses. Although one of the effective methods is ensemble learning, existing methods combine some major models which do not specialize in COVID-19. In this study, we attempted to improve the performance of a CNN for the COVID-19 classification based on chest CT volumes. The CNN model specializes in feature extraction from anisotropic chest CT volumes. We adopt the OEN, an ensemble learning method considering inter-model diversity, to boost its feature extraction ability. For the experiment, We used chest CT volumes of 1283 cases acquired in multiple medical institutions in Japan. The classification result on 257 test cases indicated that the combination could improve the classification performance.

    DOI: 10.1117/12.2653792

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  18. Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer

    Oda M., Zheng T., Hayashi Y., Otake Y., Hashimoto M., Akashi T., Aoki S., Mori K.

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE   Vol. 12465   2023

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    This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID-19) spreads over the world, causing a large number of infected patients and deaths. Sudden increase in the number of COVID-19 patients causes a manpower shortage in medical institutions. Computer-aided diagnosis (CAD) system provides quick and quantitative diagnosis results. CAD system for COVID-19 enables efficient diagnosis workflow and contributes to reduce such manpower shortage. In image-based diagnosis of viral pneumonia cases including COVID-19, both local and global image features are important because viral pneumonia cause many ground glass opacities and consolidations in large areas in the lung. This paper proposes an automated classification method of chest CT volumes for COVID-19 diagnosis assistance. MLP-Mixer is a recent method of image classification using Vision Transformer-like architecture. It performs classification using both local and global image features. To classify 3D CT volumes, we developed a hybrid classification model that consists of both a 3D convolutional neural network (CNN) and a 3D version of the MLP-Mixer. Classification accuracy of the proposed method was evaluated using a dataset that contains 1205 CT volumes and obtained 79.5% of classification accuracy. The accuracy was higher than that of conventional 3D CNN models consists of 3D CNN layers and simple MLP layers.

    DOI: 10.1117/12.2654706

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  19. Real Bronchoscopic Images-based Bronchial Nomenclature: a Preliminary Study

    Wang C., Hayashi Y., Oda M., Kitasaka T., Takabatake H., Mori M., Honma H., Natori H., Mori K.

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE   Vol. 12466   2023

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    This article describes a method for bronchial nomenclature using real bronchoscopic (RB) images and pre-built knowledge base of branches. The bronchus has a complex tree-like structure, which increases the difficulty of bronchoscopy. Therefore, a bronchoscopic navigation system is used to help physicians during examination. Conventional navigation system used preoperative CT images and real bronchoscopic images to obtain the camera pose for navigation, whose accuracy is influenced by organ deformation. We propose a bronchial nomenclature method to estimate branch names for bronchoscopic navigation. This method consists of a bronchus knowledge base construction model, a camera motion estimation module, an anatomical structure tracking module, and a branch name estimation module. The knowledge base construction module is used to find the relationship of each branch. The anatomical tracking module is used to track the bronchial orifice (BO) extracted in each RB frame. The camera motion estimation module is used to estimate the camera motion between two frames. The branch name estimation module uses the pre-built bronchus knowledge base and BO tracking results to find the name of each branch. Experimental results showed that it is possible to estimate branch names using only RB images and the pre-built knowledge base of branches.

    DOI: 10.1117/12.2654508

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  20. Priority attention network with Bayesian learning for fully automatic segmentation of substantia nigra from neuromelanin MRI

    Hu Tao, Itoh Hayato, Oda Masahiro, Saiki Shinji, Hattori Nobutaka, Kamagata Koji, Aoki Shigeki, Mori Kensaku

    MEDICAL IMAGING 2023   Vol. 12464   2023

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    Neuromelanin magnetic resonance imaging (NM-MRI) has been widely used in the diagnosis of Parkinson’s disease (PD) for its significantly enhanced contrast between the PD-related structure, the substantia nigra (SN) and surrounding tissues. To develop the computer-aided diagnosis (CAD) system of PD and reduce the labor burden of clinicians, precise and automatic segmentation of SN is becoming more and more desired. This paper proposes a novel network combining the priority gating attention and Bayesian learning for improving the accuracy of fully automatic SN segmentation from NM-MRI. Different from the conventional gated attention model, the proposed network uses the prior SN probability map for guiding the attention computation and reducing the potential disruptions introduced by the background. Additionally, to lower the risks of over-fitting and estimate the confidence scores for the segmentation results, Bayesian learning with Monte Carlo dropout is applied in the training and testing phases. The quantitative results showed that the proposed network acquired the averaged Dice score of 79.46% in comparison with the baseline model 77.93%.

    DOI: 10.1117/12.2655112

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  21. Octree Cube Constraints in PBD Method for High Resolution Surgical Simulation

    Miyazaki Rintaro, Hayashi Yuichiro, Oda Masahiro, Mori Kensaku

    MEDICAL IMAGING 2023   Vol. 12464   2023

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    This paper proposes a deformable tissue model that introduces octree lattice vertex layout and cubic constraints to the orthodox PBD (Position Based Dynamics) method. Surgical simulation is expected to provide a safe method for training in surgery, which is especially useful for preoperative education of inexperienced surgeons and/or for the case a prior attempt is required. To build a surgical simulator, it is necessary to develop organ models with deformations and interaction algorithms between surgical instruments and organ models, all of which must be performed in real time. Since existing surgical simulators focus on real-time performance, the resolution of organ models is limited. The proposed method restricts the vertex locations of the PBD method to the vertices of the octree lattice to save computation time while maintaining a high deformation resolution. To obtain appropriate results even for large deformations, three-dimensional constraints are applied to each octree cube as the constraints of the PBD method. In the simulations, we tested the overall deformation by dropping a liver model and the local deformation scene by laparoscopic clipping. As a result, we achieved deformation simulations at 26.5 fps for the model with approximately 2,672 cube elements and 20,659 vertices.

    DOI: 10.1117/12.2654092

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  22. L-former : A Lightweight Transformer for Realistic Medical Image Generation and its Application to Super-resolution

    Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Masahiro Oda, Kensaku Mori

    MEDICAL IMAGING 2023   Vol. 12464   2023

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:SPIE-INT SOC OPTICAL ENGINEERING  

    Medical image analysis approaches such as data augmentation and domain adaption need huge amounts of realistic medical images. Generating realistic medical images by machine learning is a feasible approach. We propose L-former, a lightweight Transformer for realistic medical image generation. L-former can generate more reliable and realistic medical images than recent generative adversarial networks (GANs). Meanwhile, L-former does not consume as high computational cost as conventional Transformer-based generative models. L-former uses Transformers to generate low-resolution feature vectors at shallow layers, and uses convolutional neural networks to generate high-resolution realistic medical images at deep layers. Experimental results showed that L-former outperformed conventional GANs by FID scores 33.79 and 76.85 on two datasets, respectively. We further conducted a downstream study by using the images generated by L-former to perform a super-resolution task. A high PSNR score of 27.87 proved L-former's ability to generate reliable images for super-resolution and showed its potential for applications in medical diagnosis.

    DOI: 10.1117/12.2653776

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  23. Oesophagus Achalasia Diagnosis from Esophagoscopy Based on a Serial Multi-scale Network Reviewed

    Jiang K., Oda M., Hayashi Y., Shiwaku H., Misawa M., Mori K.

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization     2023

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    DOI: 10.1080/21681163.2022.2159534

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  24. KST-Mixer: kinematic spatio-temporal data mixer for colon shape estimation Reviewed International coauthorship

    Oda M., Furukawa K., Navab N., Mori K.

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization     2023

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1080/21681163.2022.2151938

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  25. Thrombosis region extraction and quantitative analysis in confocal laser scanning microscopic image sequence in in-vivo imaging

    Wu Y., Oda M., Hayashi Y., Kawamura S., Takebe T., Mori K.

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE   Vol. 12468   2023

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    In this paper, we propose a scheme that includes automated extraction of thrombus regions and quantitative analysis of thrombosis in confocal laser scanning microscope (CLSM) blood flow image sequence. Making thrombosis model in animal models play an important role in the development of antithrombotic drugs and ascertaining thrombosis mechanisms. Making thrombosis model in cerebral cortex of mice is usually observed using a CLSM in the fluorescence mode. However, some small changes of thrombus regions are not easily observed in CLSM blood flow image sequences. In addition, it is not easy for researchers to quantitatively analyze the degree of thrombosis. Therefore, we propose a scheme to achieve automatic thrombosis region extraction and quantitative analysis. In which, our thrombosis region extraction method uses analysis of changing pattern of thrombosis regions in CLSM blood flow image sequence. Experimental results showed that our scheme can help biological researchers observe and analyze the changes of thrombosis in animal models and reduced the use of fluorescent thrombus markers.

    DOI: 10.1117/12.2654632

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  26. TriMix: A General Framework for Medical Image Segmentation from Limited Supervision

    Zheng Z., Hayashi Y., Oda M., Kitasaka T., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 13846 LNCS   page: 185 - 202   2023

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    We present a general framework for medical image segmentation from limited supervision, reducing the reliance on fully and densely labeled data. Our method is simple, jointly trains triple diverse models, and adopts a mix augmentation scheme, and thus is called TriMix. TriMix imposes consistency under a more challenging perturbation, i.e., combining data augmentation and model diversity on the tri-training framework. This straightforward strategy enables TriMix to serve as a strong and general learner learning from limited supervision using different kinds of imperfect labels. We conduct extensive experiments to show TriMix’s generic purpose for semi- and weakly-supervised segmentation tasks. Compared to task-specific state-of-the-arts, TriMix achieves competitive performance and sometimes surpasses them by a large margin. The code is available at https://github.com/MoriLabNU/TriMix.

    DOI: 10.1007/978-3-031-26351-4_12

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  27. AI画像解析による内視鏡外科手術手技のビデオ評価及び手術支援システムの構築

    安井 昭洋, 内田 広夫, 森 健策, 石田 昇平, 出家 亨一, 檜 顕成, 城田 千代栄, 小田 昌宏, 林 雄一郎

    生体医工学   Vol. Annual61 ( Abstract ) page: 127_2 - 127_2   2023

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    <p>【はじめに】術後成長発達する小児患者にとって、低侵襲手術は非常に重要である。しかし患者数は限られているため、しっかりとした手術を行うためにoff the job-training(OJT)が重要である。さらにOJTでの効率的な手技獲得には、手技を客観的に評価しfeed backを行うシステムが必須である。また安全で効率的な内視鏡手術を行うためには、臓器の位置関係の把握が必要であるため、術中ナビゲーションは重要な要件となる。これらの課題に対して、AIを用いた内視鏡手技評価および手術支援システムの構築に着手しており現状の成果を報告する。【方法と結果】食道閉鎖症モデルを用いた吻合手技を被験者に課し、各被験者の手技を最初に人の目で「check 表」「エラー項目」「時間」を用いて評価した。次にビデオから検出した鉗子の動きと人が判定した手技優劣の関係性をAIで学習させ、上位88%・下位95%の精度で手技優劣が自動判定可能となった。この結果を解析することで今まで必要だった50項目以上の肉眼チェックが、わずか7項目チェックするだけで手技の優劣を判断できることが明らかになった。現在食道閉鎖症の手術画像を用いて、食道・迷走神経・気管を深層学習させ、各種構造物の自動認識を進めている。【まとめ】AI画像解析により内視鏡手技の優劣をビデオで判定可能となった。この結果から新たに効率的な手技判断基準を定めることができた。術中ナビゲーションは現在精度のさらなる向上を目指している。</p>

    DOI: 10.11239/jsmbe.annual61.127_2

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  28. Multi-view Guidance for Self-supervised Monocular Depth Estimation on Laparoscopic Images via Spatio-Temporal Correspondence

    Li W., Hayashi Y., Oda M., Kitasaka T., Misawa K., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 14228 LNCS   page: 429 - 439   2023

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    This work proposes an innovative self-supervised approach to monocular depth estimation in laparoscopic scenarios. Previous methods independently predicted depth maps ignoring spatial coherence in local regions and temporal correlation between adjacent images. The proposed approach leverages spatio-temporal coherence to address the challenges of textureless areas and homogeneous colors in such scenes. This approach utilizes a multi-view depth estimation model to guide monocular depth estimation when predicting depth maps. Moreover, the minimum reprojection error is extended to construct a cost volume for the multi-view model using adjacent images. Additionally, a 3D consistency of the point cloud back-projected from predicted depth maps is optimized for the monocular depth estimation model. To benefit from spatial coherence, deformable patch-matching is introduced to the monocular and multi-view models to smooth depth maps in local regions. Finally, a cycled prediction learning for view synthesis and relative poses is designed to exploit the temporal correlation between adjacent images fully. Experimental results show that the proposed method outperforms existing methods in both qualitative and quantitative evaluations. Our code is available at https://github.com/MoriLabNU/MGMDepthL.

    DOI: 10.1007/978-3-031-43996-4_41

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  29. Masked Frequency Consistency for Domain-Adaptive Semantic Segmentation of Laparoscopic Images

    Zhao X., Hayashi Y., Oda M., Kitasaka T., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 14220 LNCS   page: 663 - 673   2023

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    Semantic segmentation of laparoscopic images is an important issue for intraoperative guidance in laparoscopic surgery. However, acquiring and annotating laparoscopic datasets is labor-intensive, which limits the research on this topic. In this paper, we tackle the Domain-Adaptive Semantic Segmentation (DASS) task, which aims to train a segmentation network using only computer-generated simulated images and unlabeled real images. To bridge the large domain gap between generated and real images, we propose a Masked Frequency Consistency (MFC) module that encourages the network to learn frequency-related information of the target domain as additional cues for robust recognition. Specifically, MFC randomly masks some high-frequency information of the image to improve the consistency of the network’s predictions for low-frequency images and real images. We conduct extensive experiments on existing DASS frameworks with our MFC module and show performance improvements. Our approach achieves comparable results to fully supervised learning method on the CholecSeg8K dataset without using any manual annotation. The code is available at github.com/MoriLabNU/MFC.

    DOI: 10.1007/978-3-031-43907-0_63

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  30. ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data

    Wang P., Shen C., Wang W., Oda M., Fuh C.S., Mori K., Roth H.R.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 14393   page: 311 - 321   2023

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    Developing a generalized segmentation model capable of simultaneously delineating multiple organs and diseases is highly desirable. Federated learning (FL) is a key technology enabling the collaborative development of a model without exchanging training data. However, the limited access to fully annotated training data poses a major challenge to training generalizable models. We propose “ConDistFL”, a framework to solve this problem by combining FL with knowledge distillation. Local models can extract the knowledge of unlabeled organs and tumors from partially annotated data from the global model with an adequately designed conditional probability representation. We validate our framework on four distinct partially annotated abdominal CT datasets from the MSD and KiTS19 challenges. The experimental results show that the proposed framework significantly outperforms FedAvg and FedOpt baselines. Moreover, the performance on an external test dataset demonstrates superior generalizability compared to models trained on each dataset separately. Our ablation study suggests that ConDistFL can perform well without frequent aggregation, reducing the communication cost of FL. Our implementation will be available at https://github.com/NVIDIA/NVFlare/tree/main/research/condist-fl.

    DOI: 10.1007/978-3-031-47401-9_30

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  31. 膀胱鏡画像におけるtiny-YOLOを用いた腫瘍検出

    牟田口 淳, 小田 昌宏, 猪口 淳一, 森 健策, 江藤 正俊

    生体医工学   Vol. Annual61 ( Abstract ) page: 255_2 - 255_2   2023

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    <p>【背景】膀胱癌は経尿道手術後に再発が多い腫瘍であり、膀胱鏡での腫瘍の見落としが原因とされている。内視鏡での観察は、従来の白色光(WLI)の他に、NBIを使用するが、いずれの腫瘍検出精度は検者の技量・経験に依存するため、検査の再現性・客観性が少ないことが課題である。近年、人工知能(AI)が多くの医療分野で活用されており、AIによる検査は、客観性・再現性を持った上で、エキスパートレベルと同程度の診断能を持つ可能性があるとされている。今回、WLI/NBI膀胱鏡画像を用いて、AIによる腫瘍検出の精度を検証した。【方法】2019年から2021年まで、経尿道的膀胱腫瘍切除術(TURBT)の際に、WLI/NBIを用いて観察を行った症例の手術動画から膀胱鏡画像を作成し、腫瘍を含む画像を腫瘍画像、腫瘍を含まない画像を正常画像と定義した。腫瘍画像内の膀胱腫瘍を矩形でアノテーションを行い、テストデータ用の画像を用いてAIによる感度、特異度、陽性的中率を評価した。AIでの物体検出はtiny-YOLOを用い、腫瘍検出精度の検証を行った。【結果】WLIとNBIから、それぞれ腫瘍画像をそれぞれtiny-YOLOで学習を行い、腫瘍画像(WLI: 525枚、NBI:219枚)と正常画像(WLI:98枚、NBI:108枚)で精度検証を行った。AIによる物体検出の感度/特異度/陽性的中率は、WLIで87.8%/88.8%/97.7%、NBIで82.2%/81.4%/90.0%であった。【結論】膀胱鏡画像において、AIにより比較的良好に腫瘍検出が可能であった。更なる精度改善、リアルタイム検出への課題について、文献的考察を加え報告する。</p>

    DOI: 10.11239/jsmbe.annual61.255_2

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  32. Boundary-aware feature and prediction refinement for polyp segmentation Reviewed

    Qiu Jie, Hayashi Yuichiro, Oda Masahiro, Kitasaka Takayuki, Mori Kensaku

    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION     2022.12

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    DOI: 10.1080/21681163.2022.2155579

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  33. Anatomy aware-based 2.5D bronchoscope tracking for image-guided bronchoscopic navigation Reviewed

    Wang Cheng, Oda Masahiro, Hayashi Yuichiro, Kitasaka Takayuki, Itoh Hayato, Honma Hirotoshi, Takebatake Hirotsugu, Mori Masaki, Natori Hiroshi, Mori Kensaku

    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION     2022.12

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    DOI: 10.1080/21681163.2022.2152728

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  34. Classification and visual explanation for COVID-19 pneumonia from CT images using triple learning. Reviewed

    Kato S, Oda M, Mori K, Shimizu A, Otake Y, Hashimoto M, Akashi T, Hotta K

    Scientific reports   Vol. 12 ( 1 ) page: 20840   2022.12

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    DOI: 10.1038/s41598-022-24936-6

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  35. Participating Report of MICCAI 2022 Invited

    Oda Masahiro

    Medical Imaging and Information Sciences   Vol. 39 ( 4 ) page: 78 - 81   2022.12

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:MEDICAL IMAGING AND INFORMATION SCIENCES  

    DOI: 10.11318/mii.39.78

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  36. 特集 整形外科領域における人工知能の応用 各論 深層学習を用いたMRIでの脊髄腫瘍自動位置検出システムの構築 Invited

    伊藤 定之, 中島 宏彰, 町野 正明, 世木 直喜, 小田 昌宏, 大内田 隼, 森下 和明, 森 健策, 今釜 史郎

    臨床整形外科   Vol. 57 ( 10 ) page: 1189 - 1195   2022.10

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    DOI: 10.11477/mf.1408202455

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  37. A skeleton context-aware 3D fully convolutional network for abdominal artery segmentation. Reviewed

    Zhu R, Oda M, Hayashi Y, Kitasaka T, Misawa K, Fujiwara M, Mori K

    International journal of computer assisted radiology and surgery     2022.10

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    DOI: 10.1007/s11548-022-02767-0

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  38. Class-wise confidence-aware active learning for laparoscopic images segmentation. Reviewed

    Qiu J, Hayashi Y, Oda M, Kitasaka T, Mori K

    International journal of computer assisted radiology and surgery     2022.10

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    DOI: 10.1007/s11548-022-02773-2

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  39. Pattern Analysis of Substantia Nigra in Parkinson Disease by Fifth-Order Tensor Decomposition and Multi-sequence MRI Reviewed

    Itoh H., Hu T., Oda M., Saiki S., Kamagata K., Hattori N., Aoki S., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 13594 LNCS   page: 63 - 75   2022.10

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    DOI: 10.1007/978-3-031-18814-5_7

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  40. Joint Multi Organ and Tumor Segmentation from Partial Labels Using Federated Learning Reviewed International coauthorship

    Shen C., Wang P., Yang D., Xu D., Oda M., Chen P.T., Liu K.L., Liao W.C., Fuh C.S., Mori K., Wang W., Roth H.R.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 13573 LNCS   page: 58 - 67   2022.10

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    DOI: 10.1007/978-3-031-18523-6_6

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  41. 重症COVID-19肺炎における深層学習を用いたCT画像評価と臨床パラメーターの検討 Reviewed

    坂東 皓介, 春日井 大介, 後藤 縁, 小田 昌宏, 森 健策

    日本救急医学会雑誌   Vol. 33 ( 10 ) page: 760 - 760   2022.10

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  42. Geometric Constraints for Self-supervised Monocular Depth Estimation on Laparoscopic Images with Dual-task Consistency Reviewed

    Li Wenda, Hayashi Yuichiro, Oda Masahiro, Kitasaka Takayuki, Misawa Kazunari, Mori Kensaku

    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2022, PT IV   Vol. 13434   page: 467 - 477   2022.9

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    DOI: 10.1007/978-3-031-16440-8_45

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  43. Positive-gradient-weighted object activation mapping: visual explanation of object detector towards precise colorectal-polyp localisation Reviewed

    Itoh Hayato, Misawa Masashi, Mori Yuichi, Kudo Shin-Ei, Oda Masahiro, Mori Kensaku

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY     2022.8

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    DOI: 10.1007/s11548-022-02696-y

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  44. テンソル分解を用いた黒質緻密部の3次元パターン表現に関する初期的検討

    伊東 隼人, 小田 昌宏, 斉木 臣二, 服部 信考, 鎌形 康司, 青木 茂樹, 森 健策

    日本医用画像工学会大会予稿集   Vol. 41回   page: 124 - 125   2022.7

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    黒質緻密部の3次元パターン表現に関する初期的検討について報告する.黒質緻密部における神経細胞の減少はパーキンソン病疾患者において観察される特徴のひとつである.この黒質緻密部の変化はT2強調画像や神経メラニン強調画像を介して捉えることができ,黒質緻密部の左右差や体積の減少として観察できると報告されている.一方で,得られた画像データを用いて黒質緻密部の3次元パターンの変化を計算機上で解析するためには,何らかの特徴表現が必要となる.本稿では黒質緻密部の神経メラニンMRIの信号強度比をテンソルにて表し,これらテンソルの分解に基づいた特徴表現を提案する.提案した特徴表現にて健常者・パーキンソン病患者のパターン分布を調査した結果,2つのクラスで異なる分布を表現できていることを確認した.(著者抄録)

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  45. Comprehensive Diagnostic Performance of Real-Time Characterization of Colorectal Lesions Using an Artificial Intelligence–Assisted System: A Prospective Study Reviewed

    Minegishi Y., Kudo S.E., Miyata Y., Nemoto T., Mori K., Misawa M., Mori Y., Mochida K., Akimoto Y., Ishiyama M., Ogura Y., Abe M., Sato Y., Ogawa Y., Yasuharu M., Tanaka K., Ichimasa K., Nakamura H., Ogata N., Hisayuki T., Kudo T., Hayashi T., Wakamura K., Miyachi H., Baba T., Ishida F., Itoh H., Oda M.

    Gastroenterology   Vol. 163 ( 1 ) page: 323 - 325.e3   2022.7

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    DOI: 10.1053/j.gastro.2022.03.053

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  46. Blood Vessel Segmentation from Low-Contrast and Wide-Field Optical Microscopic Images of Cranial Window by Attention-Gate-Based Network Reviewed

    Wu Yunheng, Oda Masahiro, Hayashi Yuichiro, Takebe Takanori, Nagata Shogo, Wang Cheng, Mori Kensaku

    2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2022)   Vol. 2022-June   page: 1863 - 1872   2022.6

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    DOI: 10.1109/CVPRW56347.2022.00203

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  47. BONE MARROW EDEMA SCORE IN HAND X-RAY FILM BY AI DEEP LEARNING ASSOCIATE WITH MRI BONE EDEMA IN RHEUMATOID ARTHRITIS.

    Katayama K., Pan D., Oda M., Okubo T., Mori K.

    ANNALS OF THE RHEUMATIC DISEASES   Vol. 81   page: 1773 - 1774   2022.6

  48. JACLS ALL-02 SR protocol reduced-intensity chemotherapy produces excellent outcomes in patients with low-risk childhood acute lymphoblastic leukemia

    Takahashi Y., Ishida H., Imamura T., Tamefusa K., Suenobu S., Usami I., Yumura-Yagi K., Hasegawa D., Nishimura S., Suzuki N., Hashii Y., Deguchi T., Moriya-Saito A., Kosaka Y., Kato K., Kobayashi R., Kawasaki H., Hori H., Sato A., Kudo T., Nakahata T., Oda M., Hara J., Horibe K.

    International Journal of Hematology   Vol. 115 ( 6 ) page: 890 - 897   2022.6

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    Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. As overall cure rates of childhood ALL have improved, reduction of overall treatment intensity while still ensuring excellent outcomes is imperative for low-risk patients. We report the outcomes of patients treated following the standard-risk protocol from the prospective Japan Association of Childhood Leukemia Study (JACLS) ALL-02 study, which was conducted between 2002 and 2008 for patients with newly diagnosed ALL aged 1–18 years. Of 1138 patients with B-cell precursor ALL, 388 (34.1%) were allocated to this protocol. Excellent outcomes were achieved despite the overall treatment intensity being lower than that of most contemporary protocols: 4 years event-free survival (EFS) was 92.3% and 4 years overall survival 98.2%. Patients with high hyperdiploidy (HHD) involving triple trisomy (trisomy of chromosomes 4, 10, and 17) or ETV6-RUNX1 had even better outcomes (4 years EFS 97.6% and 100%, respectively). Unique characteristics of this protocol include a selection of low-risk patients with a low initial WBC count and good early treatment response and reduction of cumulative doses of chemotherapeutic agents while maintaining dose density. In Japan, we are currently investigating the feasibility of this protocol while incorporating minimal residual disease into the patient stratification strategy.

    DOI: 10.1007/s12185-022-03315-x

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  49. SR-CycleGAN: super-resolution of clinical CT to micro-CT level with multi-modality super-resolution loss. Reviewed

    Zheng T, Oda H, Hayashi Y, Moriya T, Nakamura S, Mori M, Takabatake H, Natori H, Oda M, Mori K

    Journal of Medical Imaging   Vol. 9 ( 2 ) page: 024003   2022.3

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    DOI: 10.1117/1.JMI.9.2.024003

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  50. A cascaded fully convolutional network framework for dilated pancreatic duct segmentation Reviewed International coauthorship

    Shen Chen, Roth Holger R., Hayashi Yuichiro, Oda Masahiro, Miyamoto Tadaaki, Sato Gen, Mori Kensaku

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17 ( 2 ) page: 343 - 354   2022.2

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    DOI: 10.1007/s11548-021-02530-x

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  51. Real-time Esophagus Achalasia Detection Method for Esophagoscopy Assistance Reviewed

    MEDICAL IMAGING 2022: COMPUTER-AIDED DIAGNOSIS   Vol. 12033   2022.2

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    DOI: 10.1117/12.2613289

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  52. Uncertainty meets 3D-spatial feature in colonoscopic polyp-size determination Reviewed

    Itoh Hayato, Oda Masahiro, Jiang Kai, Mori Yuichi, Misawa Masashi, Kudo Shin-Ei, Imai Kenichiro, Ito Sayo, Hotta Kinichi, Mori Kensaku

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2022.1

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    DOI: 10.1080/21681163.2021.2004445

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  53. Impact of the clinical use of artificial intelligence-assisted neoplasia detection for colonoscopy: a large-scale prospective propensity score-matched study (with video) Reviewed

    Ishiyama Misaki, Kudo Shin-ei, Misawa Masashi, Mori Yuichi, Maeda Yasuhara, Ichimasa Katsuro, Kudo Toyoki, Hayashi Takemasa, Wakamura Kunihiko, Miyachi Hideyuki, Ishida Fumio, Itoh Hayato, Oda Masahiro, Mori Kensaku

    Gastrointestinal Endoscopy   Vol. 95 ( 1 ) page: 155 - 163   2022.1

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    DOI: 10.1016/j.gie.2021.07.022

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  54. Enhancing Model Generalization for Substantia Nigra Segmentation Using a Test-time Normalization-Based Method.

    Tao Hu, Hayato Itoh, Masahiro Oda, Yuichiro Hayashi, Zhongyang Lu, Shinji Saiki, Nobutaka Hattori, Koji Kamagata, Shigeki Aoki, Kanako K. Kumamaru, Toshiaki Akashi, Kensaku Mori

    MICCAI (8)   Vol. 13437 LNCS   page: 736 - 744   2022

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    DOI: 10.1007/978-3-031-16449-1_70

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    Other Link: https://dblp.uni-trier.de/db/conf/miccai/miccai2022-7.html#HuIOHLSHKAKAM22

  55. Spatially variant biases considered self-supervised depth estimation based on laparoscopic videos Reviewed

    Li Wenda, Hayashi Yuichiro, Oda Masahiro, Kitasaka Takayuki, Misawa Kazunari, Mori Kensaku

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2021.12

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    DOI: 10.1080/21681163.2021.2015723

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  56. Depth estimation from single-shot monocular endoscope image using image domain adaptation and edge-aware depth estimation Reviewed

    Oda Masahiro, Itoh Hayato, Tanaka Kiyohito, Takabatake Hirotsugu, Mori Masaki, Natori Hiroshi, Mori Kensaku

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2021.12

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    DOI: 10.1080/21681163.2021.2012835

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  57. Attention-Guided Pancreatic Duct Segmentation from Abdominal CT Volumes Reviewed International coauthorship

    Shen C., Roth H.R., Yuichiro H., Oda M., Miyamoto T., Sato G., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 12969 LNCS   page: 46 - 55   2021.11

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    DOI: 10.1007/978-3-030-90874-4_5

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  58. Multi-task Federated Learning for Heterogeneous Pancreas Segmentation Reviewed International coauthorship

    Shen C., Wang P., Roth H.R., Yang D., Xu D., Oda M., Wang W., Fuh C.S., Chen P.T., Liu K.L., Liao W.C., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 12969 LNCS   page: 101 - 110   2021.11

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    DOI: 10.1007/978-3-030-90874-4_10

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  59. Intestine Segmentation with Small Computational Cost for Diagnosis Assistance of Ileus and Intestinal Obstruction Reviewed

    Oda H., Hayashi Y., Kitasaka T., Takimoto A., Hinoki A., Uchida H., Suzuki K., Oda M., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 12969 LNCS   page: 3 - 12   2021.11

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    DOI: 10.1007/978-3-030-90874-4_1

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  60. COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty Reviewed

    Oda M., Zheng T., Hayashi Y., Otake Y., Hashimoto M., Akashi T., Aoki S., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 12969 LNCS   page: 88 - 97   2021.11

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    DOI: 10.1007/978-3-030-90874-4_9

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  61. Aorta-aware GAN for non-contrast to artery contrasted CT translation and its application to abdominal aortic aneurysm detection. Reviewed

    Hu T, Oda M, Hayashi Y, Lu Z, Kumamaru KK, Akashi T, Aoki S, Mori K

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17 ( 1 ) page: 97 - 105   2021.10

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    DOI: 10.1007/s11548-021-02492-0

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  62. Graph Cuts Loss to Boost Model Accuracy and Generalizability for Medical Image Segmentation Reviewed

    Zheng Zhou, Oda Masahiro, Mori Kensaku

    2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021)   Vol. 2021-October   page: 3297 - 3306   2021.10

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    DOI: 10.1109/ICCVW54120.2021.00369

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  63. Super-Resolution by Latent Space Exploration: Training with Poorly-Aligned Clinical and Micro CT Image Dataset Reviewed

    Zheng T., Oda H., Hayashi Y., Nakamura S., Oda M., Mori K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 12965 LNCS   page: 24 - 33   2021.9

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    DOI: 10.1007/978-3-030-87592-3_3

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  64. Performance improvement of weakly supervised fully convolutional networks by skip connections for brain structure segmentation Reviewed

    Sugino Takaaki, Roth Holger R., Oda Masahiro, Kin Taichi, Saito Nobuhito, Nakajima Yoshikazu, Mori Kensaku

    Medical Physics   Vol. 48 ( 11 ) page: 7215 - 7227   2021.9

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    DOI: 10.1002/mp.15192

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  65. Binary polyp-size classification based on deep-learned spatial information Reviewed

    Itoh Hayato, Oda Masahiro, Jiang Kai, Mori Yuichi, Misawa Masashi, Kudo Shin-Ei, Imai Kenichiro, Ito Sayo, Hotta Kinichi, Mori Kensaku

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16   page: 1817 - 1828   2021.9

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    DOI: 10.1007/s11548-021-02477-z

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  66. Depth-based branching level estimation for bronchoscopic navigation Reviewed

    Wang Cheng, Hayashi Yuichiro, Oda Masahiro, Kitasaka Takayuki, Takabatake Hirotsugu, Mori Masaki, Honma Hirotoshi, Natori Hiroshi, Mori Kensaku

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( 10 ) page: 1795 - 1804   2021.8

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    DOI: 10.1007/s11548-021-02460-8

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  67. Deep learning-based medical image processing and their applications beyond image processing Invited

    Oda Masahiro

    Transactions of Japanese Society for Medical and Biological Engineering   Vol. 59 ( 0 ) page: 256 - 256   2021.6

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    <p>Deep learning became an essential method of medical image processing. Deep learning solved many tasks among medical image processing, including image classification, detection, and segmentation. Many deep learning applications were proposed for eye-fundus images and radiological images among medical image modalities. Practical performances were achieved from such applications. In this presentation, we review deep learning-based medical image processing methods and their applications from their methods and image modalities. Also, we introduce new applications of deep learning in medical image processing. Deep learning-based methods process many kinds of data as their explanatory and objective variables. They can be applied to medical data, including image, text, and sensor data. We introduce some examples of such applications. We review new deep learning applications in medical image processing from the examples.</p>

    DOI: 10.11239/jsmbe.Annual59.256

  68. Artificial intelligence-assisted colonic endocytoscopy for cancer recognition: a multicenter study Reviewed

    Yuichi Mori , Shin-ei Kudo , Masashi Misawa , Kinichi Hotta , Ohtsuka Kazuo , Shoichi Saito , Hiroaki Ikematsu , Yutaka Saito , Takahisa Matsuda , Takeda Kenichi , Toyoki Kudo , Tetsuo Nemoto , Hayato Itoh , Kensaku Mori

    Endoscopy International Open     page: E1004 - E1011   2021.6

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    DOI: 10.1055/a-1475-3624

  69. Unsupervised colonoscopic depth estimation by domain translations with a Lambertian-reflection keeping auxiliary task Reviewed

    Itoh Hayato, Oda Masahiro, Mori Yuichi, Misawa Masashi, Kudo Shin-Ei, Imai Kenichiro, Ito Sayo, Hotta Kinichi, Takabatake Hirotsugu, Mori Masaki, Natori Hiroshi, Mori Kensaku

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( 6 ) page: 989 - 1001   2021.6

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    DOI: 10.1007/s11548-021-02398-x

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  70. Deep learning system for automatic detection of bladder tumors in cystoscopic images Reviewed

    Mutaguchi J., Oda M., Ueda S., Kinoshita F., Naganuma H., Matsumoto T., Lee K., Monji K., Kashiwagi K., Takeuchi A., Shiota M., Inokuchi J., Mori K., Eto M.

    EUROPEAN UROLOGY   Vol. 79   page: S1022 - S1023   2021.6

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  71. COVID-19診断支援AI開発における名古屋大学の取り組み Invited

    小田 昌宏, 鄭 通, 林 雄一郎, 森 健策

    Medical Imaging Technology   Vol. 39 ( 1 ) page: 13 - 19   2021.2

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  72. Extremely imbalanced Subarachnoid Hemorrhage detection based on DenseNet-LSTM network with Class-Balanced Loss and Transfer Learning Reviewed

    Lu Zhongyang, Oda Masahiro, Hayashi Yuichiro, Hu Tao, Itoh Hayato, Watadani Takeyuki, Abe Osamu, Hashimoto Masahiro, Jinzaki Masahiro, Mori Kensaku

    MEDICAL IMAGING 2021: COMPUTER-AIDED DIAGNOSIS   Vol. 11597   2021.2

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    DOI: 10.1117/12.2582088

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  73. Automated Detection of Spinal Schwannomas Utilizing Deep Learning Based on Object Detection from MRI Reviewed

    Sadayuki Ito, Kei Ando, Kazuyoshi Kobayashi, Hiroaki Nakashima Masahiro Oda, Masaaki Machino, Shunsuke Kanbara, Taro Inoue, Hidetoshi Yamaguchi, Hiroyuki Koshimizu, Kensaku Mori, Naoki Ishiguro, Shiro Imagama

    Spine   Vol. 46 ( 2 ) page: 95 - 100   2021.1

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    DOI: 10.1097/BRS.0000000000003749

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  74. Current status and future perspective on artificial intelligence for lower endoscopy Reviewed

    Misawa Masashi, Kudo Shin-ei, Mori Yuichi, Maeda Yasuharu, Ogawa Yushi, Ichimasa Katsuro, Kudo Toyoki, Wakamura Kunihiko, Hayashi Takemasa, Miyachi Hideyuki, Baba Toshiyuki, Ishida Fumio, Itoh Hayato, Oda Masahiro, Mori Kensaku

    DIGESTIVE ENDOSCOPY   Vol. 33 ( 2 ) page: 273 - 284   2021.1

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    DOI: 10.1111/den.13847

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  75. 医療支援AIの現状と情報横断型AIへの期待 Invited

    小田 昌宏

    日本整形外科学会雑誌   Vol. 95 ( 1 ) page: 3 - 8   2021.1

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  76. CURRENT STATUS AND FUTURE PERSPECTIVE ON ARTIFICIAL INTELLIGENCE FOR LOWER ENDOSCOPY Reviewed

    MISAWA Masashi, MIYACHI Hideyuki, BABA Toshiyuki, ISHIDA Fumio, ITOH Hayato, ODA Masahiro, MORI Kensaku, KUDO Shin-ei, MORI Yuichi, MAEDA Yasuharu, OGAWA Yushi, ICHIMASA Katsuro, KUDO Toyoki, WAKAMURA Kunihiko, HAYASHI Takemasa

    GASTROENTEROLOGICAL ENDOSCOPY   Vol. 63 ( 7 ) page: 1402 - 1416   2021.1

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    <p>The global incidence and mortality rate of colorectal cancer remains high. Colonoscopy is regarded as the gold standard examination for detecting and eradicating neoplastic lesions. However, there are some uncertainties in colonoscopy practice that are related to limitations in human performance. First, approximately one-fourth of colorectal neoplasms are missed on a single colonoscopy. Second, it is still difficult for nonexperts to perform adequately regarding optical biopsy. Third, recording of some quality indicators (e.g. cecal intubation, bowel preparation, and withdrawal speed) which are related to adenoma detection rate, is sometimes incomplete. With recent improvements in machine learning techniques and advances in computer performance, artificial intelligence-assisted computer-aided diagnosis is being increasingly utilized by endoscopists. In particular, the emergence of deep-learning, data-driven machine learning techniques have made the development of computer-aided systems easier than that of conventional machine learning techniques, the former currently being considered the standard artificial intelligence engine of computer-aided diagnosis by colonoscopy. To date, computer-aided detection systems seem to have improved the rate of detection of neoplasms. Additionally, computer-aided characterization systems may have the potential to improve diagnostic accuracy in real-time clinical practice. Furthermore, some artificial intelligence-assisted systems that aim to improve the quality of colonoscopy have been reported. The implementation of computer-aided system clinical practice may provide additional benefits such as helping in educational poorly performing endoscopists and supporting real-time clinical decision-making. In this review, we have focused on computer-aided diagnosis during colonoscopy reported by gastroenterologists and discussed its status, limitations, and future prospects.</p>

    DOI: 10.11280/gee.63.1402

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  77. Report on the First JSCAS AI Challenge Invited

    Journal of Japan Society of Computer Aided Surgery   Vol. 23 ( 2 ) page: 74 - 75   2021

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    DOI: 10.5759/jscas.23.74

  78. Object Detection method by deep learning for diagnosing bladder tumors in cystoscopic images

    Mutaguchi Jun, Oda Masahiro, Kobayashi Satoshi, Inokuchi Junichi, Mori Kensaku, Eto Masatoshi

    Transactions of Japanese Society for Medical and Biological Engineering   Vol. 59 ( 0 ) page: 299 - 299   2021

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    <p>The overlooking bladder tumors during transurethral resection of bladder tumor (TURBT) causes high intravesical recurrence rate. The conventional White light imaging(WLI) and Narrow-band imaging (NBI) were subjective and poor reproducibility due to depending on doctor's experience and skills. Recently, image recognition using artificial intelligence (AI) has been applied for diagnostic imaging and achieving a good performance result, however the feasibility of cystoscopy with AI is still unknown. In this study, we constructed an object detection system based on the AI architecture. We prospectively obtained cystoscopic images from patients who underwent TURBT, and divided these images as the training data and test data. The sensitivity, specificity and Positive predictive value of WLI and NBI were 84.6%, 76.9% and 90.8%, and 78.1%, 97.1% and 95.8%, respectively. Our system has the possibility to improve detection rates of the bladder tumors during cystoscopy, and might be beneficial to reduce recurrence rate of bladder tumors.</p>

    DOI: 10.11239/jsmbe.Annual59.299

  79. An Introduction to Deep Learing in Image Recognition(2):  Configuration of GPU Environments and Application to Image Segmentation Invited

    HARA Takeshi, ODA Masahiro

    Medical Imaging Technology   Vol. 39 ( 3 ) page: 124 - 130   2021

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    <p>In order to set up a practical experiment and research environment for deep learning, it is necessary to build an computing environment using GPU. This is because the calculation speed is several tens of times faster than the calculation using only the CPU. In this course, we will explain how to build a GPU environment and clarify how much the calculation time changes, using image segmentation as an example. At the same time, the method of image segmentation using U-Net model and the construction of the label data are also mentioned.</p>

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  80. Towards Explainable Artificial Intelligence: Introduction Invited

    FUJIYOSHI Hironobu, ODA Masahiro

    Medical Imaging Technology   Vol. 39 ( 3 ) page: 97 - 98   2021

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  81. Robust endocytoscopic image classification based on higher-order symmetric tensor analysis and multi-scale topological statistics Reviewed

    Hayato Itoh, Yukitaka Nimura, Yuichi Mori, Masashi Misawa, Shin-Ei Kudo, Kinichi Hotta, Kazuo Ohtsuka, Shoichi Saito, Yutaka Saito, Hiroaki Ikematsu, Yuichiro Hayashi, Masahiro Oda, Kensaku Mori

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 15 ( 12 ) page: 2049 - 2059   2020.12

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  82. Synthetic laparoscopic video generation for machine learning-based surgical instrument segmentation from real laparoscopic video and virtual surgical instruments Reviewed

    Ozawa Takuya, Hayashi Yuichiro, Oda Hirohisa, Oda Masahiro, Kitasaka Takayuki, Takeshita Nobuyoshi, Ito Masaaki, Mori Kensaku

    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION     2020.11

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  83. 大腸鏡画像にYOLO-v3を用いた、穿孔の検出と局在化の比率損失設計に関する予備的研究(Preliminary Study of Loss-Functions Design for Detection and Localization of Perforations with YOLO-v3 in Colonoscopic Images)

    蒋 凱, 伊東 隼人, 小田 昌宏, 奥村 大志, 森 悠一, 三澤 将史, 林 武雅, 工藤 進英, 森 健策

    日本コンピュータ外科学会誌   Vol. 22 ( 4 ) page: 348 - 349   2020.11

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  84. SUN database 大腸ポリープ自動検出器の精度評価に向けた試験用画像

    伊東 隼人, 三澤 将史, 森 悠一, 小田 昌宏, 工藤 進英, 森 健策

    日本コンピュータ外科学会誌   Vol. 22 ( 4 ) page: 346 - 347   2020.11

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  85. 【多元計算解剖学の診断・治療・医工学への展開】人工知能に基づく医療機器EndoBRAINの臨床導入 薬事承認取得・保険算定への挑戦

    森 悠一, 工藤 進英, 三澤 将史, 伊東 隼人, 小田 昌宏, 森 健策

    MEDICAL IMAGING TECHNOLOGY   Vol. 38 ( 5 ) page: 213 - 216   2020.11

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  86. 腹腔鏡動画像用オンラインアノテーションツールの開発

    屠 芸豪, 伊東 隼人, 小澤 卓也, 小田 昌宏, 竹下 修由, 伊藤 雅昭, 森 健策

    日本コンピュータ外科学会誌   Vol. 22 ( 4 ) page: 306 - 307   2020.11

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  87. Artificial Intelligence System to Determine Risk of T1 Colorectal Cancer Metastasis to Lymph Node. Reviewed

    Kudo SE, Ichimasa K, Villard B, Mori Y, Misawa M, Saito S, Hotta K, Saito Y, Matsuda T, Yamada K, Mitani T, Ohtsuka K, Chino A, Ide D, Imai K, Kishida Y, Nakamura K, Saiki Y, Tanaka M, Hoteya S, Yamashita S, Kinugasa Y, Fukuda M, Kudo T, Miyachi H, Ishida F, Itoh H, Oda M, Mori K

    Gastroenterology     2020.9

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  88. Prediction of dose distribution from luminescence image of water using a deep convolutional neural network for particle therapy Reviewed

    Takuya Yabe, Seiichi Yamamoto, Masahiro Oda, Kensaku Mori, Toshiyuki Toshito, Takashi Akagi

    MEDICAL PHYSICS   Vol. 47 ( 9 ) page: 3882 - 3891   2020.9

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  89. 大腸内視鏡における穿孔の自動検出および位置推定に関する予備的検討

    蒋 凱, 伊東 隼人, 小田 昌宏, 奥村 大志, 森 悠一, 三澤 将史, 林 武雅, 工藤 進英, 森 健策

    日本医用画像工学会大会予稿集   Vol. 39回   page: 29 - 29   2020.9

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  90. 位置特徴量とマルチスケール特徴量による胃壁マイクロCT像からの胃壁の層構造及び腫瘍の抽出

    御手洗 翠, 小田 紘久, 杉野 貴明, 守谷 享泰, 伊東 隼人, 小田 昌宏, 小宮山 琢真, 古川 和宏, 宮原 良二, 藤城 光弘, 森 雅樹, 高畠 博嗣, 名取 博, 森 健策

    日本医用画像工学会大会予稿集   Vol. 39回   page: 569 - 572   2020.9

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    本稿では,Spherical K-means(SpK)により抽出された複数スケールの特徴量と位置特徴量を用いた胃壁μCT画像からの粘膜層,粘膜下層,筋層及び腫瘍の抽出手法について報告する.胃壁のμCT画像から解剖学的構造を抽出することで腫瘍の立体構造把握が可能である.従来手法では複数スケールの特徴抽出フィルタをSpKによって学習し,パッチから特徴抽出を行った.その後得られた特徴量に基づいてSVMによって分類を行っていた.しかし,SpKにより生成された特徴抽出フィルタは濃度値に基づく特徴量を抽出するため,粘膜層と筋層のように濃度値が類似した領域同士の特徴量が近しい値になる.本手法ではSpKにより得られる複数スケールの特徴量にパッチの位置特徴量を追加して分類する事によって,濃度値に基づく特徴量では分類できない領域の分類を可能にする.パッチの位置特徴量としてパッチの中心座標を用いる.本手法を胃壁μCT像に適用した結果,粘膜層,粘膜下層,筋層及び腫瘍の抽出に対するDICE係数は68.3%,63.2%,82.2%,69.1%であった.特に従来手法と比べ,腫瘍の抽出に対するDICE係数は26.1%向上した.(著者抄録)

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  91. A visual SLAM-based bronchoscope tracking scheme for bronchoscopic navigation Reviewed

    Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Benjamin Villard, Takayuki Kitasaka, Hirotsugu Takabatake, Masaki Mori, Hirotoshi Honma, Hiroshi Natori, Kensaku Mori

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 15 ( 10 ) page: 1619 - 1630   2020.8

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  92. Development of a computer-aided detection system for colonoscopy and a publicly accessible large colonoscopy video database (with video). Reviewed

    Misawa M, Kudo SE, Mori Y, Hotta K, Ohtsuka K, Matsuda T, Saito S, Kudo T, Baba T, Ishida F, Itoh H, Oda M, Mori K

    Gastrointestinal endoscopy     2020.7

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  93. A deformable model for navigated laparoscopic gastrectomy based on finite elemental method Reviewed

    Chen Tao, Wei Guodong, Xu Lili, Shi Weili, Xu Yikai, Zhu Yongyi, Hayashi Yuichiro, Oda Hirohisa, Oda Masahiro, Hu Yanfeng, Yu Jiang, Jiang Zhengang, Li Guoxin, Mori Kensaku

    MINIMALLY INVASIVE THERAPY & ALLIED TECHNOLOGIES   Vol. 29 ( 4 ) page: 210 - 216   2020.7

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    DOI: 10.1080/13645706.2019.1625926

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  94. Artificial Intelligence-assisted System Improves Endoscopic Identification of Colorectal Neoplasms Reviewed

    Kudo Shin-ei, Misawa Masashi, Mori Yuichi, Hotta Kinichi, Ohtsuka Kazuo, Ikematsu Hiroaki, Saito Yutaka, Takeda Kenichi, Nakamura Hiroki, Ichimasa Katsuro, Ishigaki Tomoyuki, Toyoshima Naoya, Kudo Toyoki, Hayashi Takemasa, Wakamura Kunihiko, Baba Toshiyuki, Ishida Fumio, Inoue Haruhiro, Itoh Hayato, Oda Masahiro, Mori Kensaku

    CLINICAL GASTROENTEROLOGY AND HEPATOLOGY   Vol. 18 ( 8 ) page: 1874 - +   2020.7

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    DOI: 10.1016/j.cgh.2019.09.009

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  95. PREDICTION OF LYMPH NODE METASTASIS IN T2 COLORECTAL CANCER BASED ON ARTIFICIAL INTELLIGENCE -PROPOSAL OF AN INDICATION FOR FUTURE FULL-THICKNESS ENDOSCOPIC RESECTION- Reviewed

    Ichimasa Katsuro, Kudo Shinei, Benjamin Villard, Nakahara Kenta, Mori Yuichi, Misawa Masashi, Yasuharu Maeda, Toyoshima Naoya, Ogata Noriyuki, Kudo Toyoki, Hayashi Takemasa, Wakamura Kunihiko, Miyachi Hideyuki, Sawada Naruhiko, Itoh Hayato, Oda Masahiro, Mori Kensaku, Ishida Fumio

    GASTROINTESTINAL ENDOSCOPY   Vol. 91 ( 6 ) page: AB43 - AB43   2020.6

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  96. 内視鏡診断支援ソフトウェアEndoBRAINの臨床的有効性および医療費抑制効果

    森 悠一, 工藤 進英, 三澤 将史, 武田 健一, 前田 康晴, 小川 悠史, 一政 克朗, 若村 邦彦, 林 武雅, 工藤 豊樹, 宮地 英行, 馬場 俊之, 伊東 隼人, 小田 昌宏, 森 健策

    日本大腸検査学会雑誌   Vol. 36 ( 2 ) page: 77 - 82   2020.5

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    EndoBRAIN(製造:サイバーネットシステム株式会社・販売:オリンパス株式会社)は、人工知能による診断支援システムとして、本邦初の薬機法承認を得た医療機器である。EndoBRAINは超拡大内視鏡(CF-H290ECI、オリンパス株式会社)によって取得される520倍の拡大画像をAIが解析することで、大腸病変が腫瘍なのかどうかを瞬時に予測し、医師に情報提供を行う。2012年から開始したEndoBRAINの研究開発は、昭和大学-名古屋大学-サイバーネットシステム株式会社での医工産連携のもと、日本医療研究開発機構(AMED)からのサポート下に継続的に実施され、2018年12月に薬機法承認を取得した。EndoBRAINの臨床的有用性については、2018年に791症例を対象とした大規模前向き試験の結果が公表されており、感度92.7%で腫瘍の鑑別が可能であると報告されている。また、最近公表された前向き試験の副次解析結果によると、EndoBRAINを使用することで、本来切除すべきでない非腫瘍性ポリープの治療件数を抑制することができるため、これにより最大164億円/年の医療費が削減しうることが分かってきた。本稿では、EndoBRAINの特徴・使用法、および薬機法承認取得までの経緯を紹介するとともに、その臨床的有用性および期待される医療費抑制効果について、最新の研究成果を総括する。(著者抄録)

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  97. AIによるSSA/Pの超拡大内視鏡診断

    小川 悠史, 工藤 進英, 森 悠一, 三澤 将史, 片岡 伸一, 前田 康晴, 一政 克朗, 石垣 智之, 工藤 豊樹, 若村 邦彦, 林 武雅, 馬場 俊之, 石田 文生, 伊東 隼人, 小田 昌宏, 森 健策

    日本大腸検査学会雑誌   Vol. 36 ( 2 ) page: 125 - 125   2020.5

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  98. Super-resolution of clinical CT volumes with modified CycleGAN using micro CT volumes

    Tong ZHENG, Hirohisa ODA, Takayasu MORIYA, Takaaki SUGINO, Shota NAKAMURA, Masahiro ODA, Masaki MORI, Hirotsugu TAKABATAKE, Hiroshi NATORI, Kensaku MORI

    CoRR   Vol. abs/2004.03272   page: 454 - 459   2020.4

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    This paper presents a super-resolution (SR) method with unpaired training
    dataset of clinical CT and micro CT volumes. For obtaining very detailed
    information such as cancer invasion from pre-operative clinical CT volumes of
    lung cancer patients, SR of clinical CT volumes to $\m$}CT level is desired.
    While most SR methods require paired low- and high- resolution images for
    training, it is infeasible to obtain paired clinical CT and {\mu}CT volumes. We
    propose a SR approach based on CycleGAN, which could perform SR on clinical CT
    into $\mu$CT level. We proposed new loss functions to keep cycle consistency,
    while training without paired volumes. Experimental results demonstrated that
    our proposed method successfully performed SR of clinical CT volume of lung
    cancer patients into $\mu$CT level.

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  99. How Far Will Clinical Application of AI Applications Advance for Colorectal Cancer Diagnosis? Reviewed

    Mori Yuichi, Kudo Shin-ei, Misawa Masashi, Takeda Kenichi, Kudo Toyoki, Itoh Hayato, Oda Masahiro, Mori Kensaku

    JOURNAL OF THE ANUS RECTUM AND COLON   Vol. 4 ( 2 ) page: 47 - 50   2020.4

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  100. Artificial intelligence for magnifying endoscopy, endocytoscopy, and confocal laser endomicroscopy of the colorectum

    Mori Yuichi, Kudo Shin-ei, Misawa Masashi, Itoh Hayato, Oda Masahiro, Mori Kensaku

    TECHNIQUES AND INNOVATIONS IN GASTROINTESTINAL ENDOSCOPY   Vol. 22 ( 2 ) page: 56 - 60   2020.4

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    Because magnifying endoscopy is considered to be more accurate at predicting the histology of colorectal polyps than nonmagnifying endoscopy, it has been attracting a lot of attention, especially in Japan. However, use of magnifying endoscopy is not yet widespread because of its limited availability and the difficulty in interpreting the acquired images. Application of artificial intelligence (AI) is now changing this situation because it helps less-skilled endoscopists to accurately interpret magnified images. Research in this field initially focused on magnifying endoscopy with narrow-band imaging as the target of AI. Most previously published retrospective studies have reported over 90% sensitivity in differentiation of neoplastic lesions; however, automatically indicating the region of interest (ROI) of the polyps that AI should analyze has been found to be challenging. To address this practical problem, some researchers have started to adopt contact endomicroscopy as a target for AI. Contact endomicroscopy includes endocytoscopy (520-fold magnification, Olympus, Tokyo, Japan) and confocal laser endomicroscopy (1000-fold magnification, Mauna Kea, Paris, France). These forms of contact endomicroscopy provide ultramagnified images that make it unnecessary to manually select the ROI because the entire image acquired by contact endomicroscopy is the ROI of the targeted polyps. This strength of contact endomicroscopy has contributed to early implementation of this technology into clinical practice, which may change the utility of magnifying endoscopy in clinical settings and help increase its use globally in the near future.

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  101. Cardiac fiber tracking on super high-resolution CT images: a comparative study Reviewed

    Hirohisa Oda, Holger R. Roth, Takaaki Sugino, Naoki Sunaguchi, Noriko Usami, Masahiro Oda, Daisuke Shimao, Shu Ichihara, Tetsuya Yuasa, Masami Ando, Toshiaki Akita, Yuji Narita, Kensaku Mori

    JOURNAL OF MEDICAL IMAGING   Vol. 7 ( 2 ) page: 026001   2020.3

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  102. Tensor-cut: A tensor-based graph-cut blood vessel segmentation method and its application to renal artery segmentation Reviewed

    Chenglong Wang, Masahiro Oda, Yuichiro Hayashi, Yasushi Yoshino, Tokunori Yamamoto, Alejandro F. Frangi, Kensaku Mori

    MEDICAL IMAGE ANALYSIS   Vol. 60   page: 101623   2020.2

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  103. Micro-computed tomography images of lung adenocarcinoma: detection of lepidic growth patterns Reviewed

    Nakamura Shota, Mori Kensaku, Iwano Shingo, Kawaguchi Koji, Fukui Takayuki, Hakiri Shuhei, Ozeki Naoki, Oda Masahiro, Yokoi Kohei

    NAGOYA JOURNAL OF MEDICAL SCIENCE   Vol. 82 ( 1 ) page: 25 - 31   2020.2

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  104. Clinical Application of EndoBRAIN, a Medical Device Adopting Artificial Intelligence: Challenges to Obtain Regulatory Approval and Insurance Reimbursement Invited

    MORI Yuichi, KUDO Shin-ei, MISAWA Masashi, ITOH Hayato, ODA Masahiro, MORI Kensaku

    Medical Imaging Technology   Vol. 38 ( 5 ) page: 213-216   2020

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    <p>EndoBRAIN (Cybernet System Corp.; Olympus Corp., Tokyo) is the computer-aided diagnostic system supportedby artificial intelligence (AI) that allows real-time identification of colorectal polyps. EndoBRAIN was the firstly approved medical device in the field of AI in Japan. This regulatory approval was achieved by the close collaboration among medical researchers, engineering researchers, industrial partners, and public funding bodies. This review article shows the overview of EndoBRAIN including its design, performance, and results in clinical trials. In addition, our approaches to regulatory approval and insurance reimbursement, which unfortunately has not been granted, are also introduced.</p>

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  105. Organ Segmentation From Full-size CT Images Using Memory-Efficient FCN Reviewed

    Wang Chenglong, Oda Masahiro, Mori Kensaku

    MEDICAL IMAGING 2020: COMPUTER-AIDED DIAGNOSIS   Vol. 11314   2020

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  106. Usefulness of fine-tuning for deep learning based multi-organ regions segmentation method from non-contrast CT volumes using small training dataset Reviewed

    Hayashi Yuichiro, Shen Chen, Roth Holger R., Oda Masahiro, Misawa Kazunari, Jinzaki Masahiro, Hashimoto Masahiro, Kumamaru Kanako K., Aoki Shigeki, Mori Kensaku

    MEDICAL IMAGING 2020: COMPUTER-AIDED DIAGNOSIS   Vol. 11314   2020

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  107. Visualising decision-reasoning regions in computer-aided pathological pattern diagnosis of endoscytoscopic images based on CNN weights analysis Reviewed

    Itoh Hayato, Lu Zhongyang, Mori Yuichi, Misawa Masashi, Oda Masahiro, Kudo Shin-ei, Mori Kensaku

    MEDICAL IMAGING 2020: COMPUTER-AIDED DIAGNOSIS   Vol. 11314   2020

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  108. Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images Reviewed

    Oda Hirohisa, Nishio Kohei, Kitasaka Takayuki, Amano Hizuru, Takimoto Aitaro, Uchida Hiroo, Suzuki Kojiro, Itoh Hayato, Oda Masahiro, Mori Kensaku

    MEDICAL IMAGING 2020: COMPUTER-AIDED DIAGNOSIS   Vol. 11314   2020

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  109. Deep Learning in Surgical Assistance Invited

    Oda Masahiro

    Journal of Japan Society of Computer Aided Surgery   Vol. 22 ( 1 ) page: 54-58   2020

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    DOI: 10.5759/jscas.22.54

  110. Spatial information-embedded fully convolutional networks for multi-organ segmentation with improved data augmentation and instance normalization Reviewed

    Chen Shen, Chenglong Wang, Holger R. Roth, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE   Vol. 11313   2020

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  111. Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database Reviewed

    Tong Zheng, Hirohisa Oda, Takayasu Moriya, Takaaki Sugino, Shota Nakamura, Masahiro Oda, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE   Vol. 11313   2020

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  112. Improved visual SLAM for bronchoscope tracking and registration with pre-operative CT images Reviewed

    Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Takayuki Kitasaka, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    Proceedings of SPIE - The International Society for Optical Engineering   Vol. 11315   2020

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    DOI: 10.1117/12.2549949

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  113. Automated eye disease classification method from anterior eye image using anatomical structure focused image classification technique Reviewed

    Oda Masahiro, Yamaguchi Takefumi, Fukuoka Hideki, Ueno Yuta, Mori Kensaku

    MEDICAL IMAGING 2020: COMPUTER-AIDED DIAGNOSIS   Vol. 11314   2020

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    DOI: 10.1117/12.2549951

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  114. Realistic Endoscopic Image Generation Method Using Virtual-to-real Image-domain Translation Reviewed

    Masahiro Oda, Kiyohito Tanaka, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    Healthcare Technology Letters   Vol. 6 ( 6 ) page: 214 - 219   2019.12

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    DOI: 10.1049/htl.2019.0071

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  115. Abdominal artery segmentation method from CT volumes using fully convolutional neural network Reviewed

    Masahiro Oda, Holger R. Roth, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 14 ( 12 ) page: 2069 - 2081   2019.12

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    DOI: 10.1007/s11548-019-02062-5

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  116. Stable polyp-scene classification via subsampling and residual learning from an imbalanced large dataset Reviewed

    Hayato Itoh, Holger Roth, Masahiro Oda, Masashi Misawa, Yuichi Mori, Shin-Ei Kudo, Kensaku Mori

    HEALTHCARE TECHNOLOGY LETTERS   Vol. 6 ( 6 ) page: 237 - 242   2019.12

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    DOI: 10.1049/htl.2019.0079

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  117. Artificial intelligence and computer-aided diagnosis for colonoscopy: where do we stand now?

    Kudo Shin-ei, Mori Yuichi, Abdel-aal Usama M., Misawa Masashi, Itoh Hayato, Oda Masahiro, Mori Kensaku

    TRANSLATIONAL GASTROENTEROLOGY AND HEPATOLOGY     2019.11

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    DOI: 10.21037/tgh.2019.12.14

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  118. 超拡大大腸内視鏡画像における施設間データ分布の差異を考慮した分類法に関する初期的検討

    伊東 隼人, 森 悠一, 三澤 将史, 小田 昌宏, 工藤 進英, 森 健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 ) page: 332 - 333   2019.11

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  119. 臨床肺CT画像と切除肺マイクロCT画像の初期位置合わせ手法の検討 Reviewed

    波多腰 慎矢, 小田 紘久, 杉野 貴明, 林 雄一郎, Roth Holger R., 中村 彰太, 小田 昌宏, 森 雅樹, 高畠 博嗣, 名取 博, 森 健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 ) page: 318 - 319   2019.11

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  120. 内視鏡的粘膜下層剥離術中の自動穿孔検出に関する初期的検討

    大石 仁美, 伊東 隼人, 森 悠一, 三澤 将史, 林 武雅, 奥村 大志, 小田 昌宏, 工藤 進英, 森 健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 ) page: 232 - 233   2019.11

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  121. Grad-CAMを用いた脳CT像からのくも膜下出血の出血領域可視化に関する検討(Visualization of subarachnoid hemorrhage area from brain CT images using Grad-CAM)

    魯 仲陽, 伊東 隼人, 小田 昌宏, 林 雄一郎, 渡谷 岳行, 阿部 修, 橋本 正弘, 陣崎 雅弘, 森 健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 ) page: 229 - 230   2019.11

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  122. グラフ畳み込みニューラルネットワークによる腹部動脈血管名自動命名におけるデータ拡張による精度改善

    日比 裕太, 林 雄一郎, 北坂 孝幸, 伊東 隼人, 小田 昌宏, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 ) page: 226 - 227   2019.11

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  123. 小児腸閉塞患者のCT像における電子洗浄手法の評価

    西尾 光平, 小田 紘久, 千馬 耕亮, 北坂 孝幸, 林 雄一郎, 伊東 隼人, 小田 昌宏, 檜 顕成, 内田 広夫, 森 健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 ) page: 321 - 321   2019.11

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  124. 特集 今知りたい、AIの歴史とこれから ディープラーニング実践の環境構築

    小田 昌宏

    臨床画像   Vol. 35 ( 10 ) page: 1120 - 1128   2019.10

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    DOI: 10.18885/j01843.2020039296

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  125. Precise estimation of renal vascular dominant regions using spatially aware fully convolutional networks, tensor-cut and Voronoi diagrams Reviewed

    Chenglong Wang, Holger R. Roth, Takayuki Kitasaka, Masahiro Oda, Yuichiro Hayashi, Yasushi Yoshino, Tokunori Yamamoto, Naoto Sassa, Momokazu Goto, Kensaku Mori

    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS   Vol. 77   page: 101642   2019.10

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    DOI: 10.1016/j.compmedimag.2019.101642

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  126. SSA/Pの人工知能支援下超拡大内視鏡診断

    小川 悠史, 工藤 進英, 森 悠一, 三澤 将史, 武田 健一, 片岡 伸一, 前田 康晴, 一政 克朗, 工藤 豊樹, 若村 邦彦, 林 武雅, 馬場 俊之, 石田 文生, 伊東 隼人, 小田 昌宏, 森 健策

    Gastroenterological Endoscopy   Vol. 61 ( Suppl.2 ) page: 2167 - 2167   2019.10

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  127. A view of three dimensional unit structures of alveoli in peripheral lung Reviewed

    Natori Hiroshi, Takabatake Hirotsugu, Mori Masaki, Oda Masahiro, Mori Kensaku, Koba Hiroyuki, Takahashi Hiroki

    EUROPEAN RESPIRATORY JOURNAL   Vol. 54   2019.9

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    DOI: 10.1183/13993003.congress-2019.PA3168

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  128. Artificial intelligence and colonoscopy: Current status and future perspectives Reviewed

    Kudo Shin-ei, Mori Yuichi, Misawa Masashi, Takeda Kenichi, Kudo Toyoki, Itoh Hayato, Oda Masahiro, Mori Kensaku

    DIGESTIVE ENDOSCOPY   Vol. 31 ( 4 ) page: 363 - 371   2019.7

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    DOI: 10.1111/den.13340

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  129. Artificial intelligence and upper gastrointestinal endoscopy: Current status and future perspective Reviewed

    Yuichi Mori, Shin‐ei Kudo, Hussein Ebaid Naeem Mohmed, Masashi Misawa, Noriyuki Ogata, Hayato Itoh, Masahiro Oda, Kensaku Mori

    DIGESTIVE ENDOSCOPY   Vol. 31 ( 4 ) page: 378 - 388   2019.7

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    DOI: 10.1111/den.13317

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  130. 3D fully convolutional network を用いた腎腫瘍の定量評価における初期検討

    王 成龍, 小田 昌宏, 林 雄一郎, 佐々 直人, 山本 徳則, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP5-23   2019.7

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  131. AMED 大規模データベースを用いた CT 画像解析と病変検出への応用

    森 健策, 小田 昌宏

    第38回日本医用画像工学会大会予稿集     page: SY1-5   2019.7

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  132. Polyp size classification in colorectal cancer using a Siamese network

        page: OP2-14   2019.7

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  133. 深層学習を用いた非造影 CT 画像からの複数臓器領域の抽出に関する検討

    林 雄一郎, 申 忱, Roth Holger, 小田 昌宏, 三澤 一成, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP5-14   2019.7

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  134. 深層学習を用いた腹腔鏡手術動画像の出血領域自動セグメンテーション

    山本 翔太, 小田 紘久, 林 雄一郎, 北坂 孝幸, 小田 昌宏, 伊藤 雅昭, 竹下 修由, 森 健策

    第38回日本医用画像工学会大会予稿     page: OP4-13   2019.7

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  135. 深層学習における学習データセット規模拡大に応じた分類精度向上に関する実験的検討 ~超拡大大腸内視鏡画像における腫瘍性病変分類に向けた特徴量抽出~

    伊東 隼人, 森 悠一, 三澤 将史, 小田 昌宏, 工藤 進英, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP1-24   2019.7

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  136. 少量のラベルデータを用いた学習によるイレウス症例 CT 像における拡張腸管の自動抽出

    小田 紘久, 西尾 光平, 北坂 孝幸, 天野 日出, 千馬 耕亮, 内田 広夫, 鈴木 耕次郞, 伊東 隼人, 小田 昌宏, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP1-15   2019.7

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  137. 小児腸閉塞患者の CT 像における CycleGAN を用いた電子洗浄手法の検討

    西尾 光平, 小田 紘久, 千馬 耕亮, 北坂 孝幸, 伊東 隼人, 小田 昌宏, 檜 顕成, 内田 広夫, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP3-20   2019.7

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  138. グラフ畳み込みニューラルネットワークを用いた腹部動脈血管名自動命名の初期検討

    日比 裕太, 林 雄一郎, 北坂 孝幸, 伊東 隼人, 小田 昌宏, 三澤 一成, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP5-11   2019.7

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  139. 移学習を用いた腹部 thick-slice CT 像における多臓器領域の自動抽出の初期検討

    申 忱, ロス ホルガー, 林 雄一郎, 小田 紘久, 小田 昌宏, 三澤 一成, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP4-15   2019.7

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  140. 表現学習と SVM による胃壁マイクロ CT 像の半教師ありセグメンテーション手法

    御手洗 翠, 小田 紘久, 杉野 貴明, 守谷 享泰, 伊東 隼人, 小田 昌宏, 小宮山 琢真, 森 雅樹, 高畠 博嗣, 名取 博, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP2-08   2019.7

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  141. 腹腔鏡動画像からの Fully Convolutional Network による血管領域抽出

    盛満 慎太郎, 小澤 卓也, 北坂 孝幸, 林 雄一郎, 小田 昌宏, 伊藤 雅昭, 竹下 修由, 三澤 一成, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP3-12   2019.7

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  142. ARTIFICIAL INTELLIGENCE-ASSISTED POLYP DETECTION SYSTEM FOR COLONOSCOPY, BASED ON THE LARGEST AVAILABLE COLLECTION OF CLINICAL VIDEO DATA FOR MACHINE LEARNING Reviewed

    Misawa Masashi, Kudo Shinei, Mori Yuichi, Cho Tomonari, Kataoka Shinichi, Maeda Yasuharu, Ogawa Yushi, Takeda Kenichi, Nakamura Hiroki, Ichimasa Katsuro, Toyoshima Naoya, Ogata Noriyuki, Kudo Toyoki, Hisayuki Tomokazu, Hayashi Takemasa, Wakamura Kunihiko, Baba Toshiyuki, Ishida Fumio, Itoh Hayato, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 89 ( 6 ) page: AB646 - AB647   2019.6

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  143. PERFORMANCE OF NON-EXPERT ENDOSCOPISTS IN OPTICAL BIOPSY OF DIMINUTIVE COLORECTAL POLYPS WITH REAL-TIME USE OF ARTIFICIAL INTELLIGENCE Reviewed

    Mori Yuichi, Kudo Shinei, Misawa Masashi, Kataoka Shinichi, Takeda Kenichi, Suzuki Kenichi, Ichimasa Katsuro, Ogawa Yushi, Maeda Yasuharu, Hayashi Takemasa, Wakamura Kunihiko, Kudo Toyoki, Ishida Fumio, Inoue Haruhiro, Itoh Hayato, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 89 ( 6 ) page: AB89 - AB89   2019.6

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  144. COMPUTER-AIDED DIAGNOSIS FOR SAMLL COLORECTAL LESIONS: A MULTI-CENTER VALIDATION "ENDOBRAIN STUDY" DESIGNED TO OBTAIN REGULATORY APPROVAL Reviewed

    Hotta Kinichi, Kudo Shinei, Mori Yuichi, Ikematsu Hiroaki, Saito Yutaka, Ohtsuka Kazuo, Misawa Masashi, Itoh Hayato, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 89 ( 6 ) page: AB76 - AB76   2019.6

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  145. ARTIFICIAL INTELLIGENCE-ASSISTED POLYP DETECTION SYSTEM FOR COLONOSCOPY, BASED ON THE LARGEST AVAILABLE COLLECTION OF CLINICAL VIDEO DATA FOR MACHINE LEARNING Reviewed

    Misawa Masashi, Kudo Shinei, Mori Yuichi, Cho Tomonari, Kataoka Shinichi, Maeda Yasuharu, Ogawa Yushi, Takeda Kenichi, Nakamura Hiroki, Ichimasa Katsuro, Toyoshima Naoya, Ogata Noriyuki, Kudo Toyoki, Hisayuki Tomokazu, Hayashi Takemasa, Wakamura Kunihiko, Baba Toshiyuki, Ishida Fumio, Itoh Hayato, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 89 ( 6 ) page: AB646-AB647   2019.6

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  146. Evaluation on econstruction accuracy of visual SLAM based bronchoscope tracking

    C. Wang, Masahiro Oda, Yuichiro Hayashi, Takayuki Kitasaka, Hayato Itoh, H. Honma, H. Takabatake, M. Mori, H. Natori, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: S24-25   2019.6

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  147. 深層学習を用いた脳CT像からの出血検出におけるデータ拡張とネットワーク構造の影響に関する考察

    魯 仲陽, 小田 昌宏, 鄭 通, 申 忱, 胡 涛, 渡谷 岳行, 阿部 修, 橋本 正弘, 陣崎 雅弘, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 119 ( 51 ) page: 65-70   2019.5

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  148. Development of a New Laparoscopic Detection System for Gastric Cancer Using Near-Infrared Light-Emitting Clips with Glass Phosphor Reviewed

    Inada Shunko A, Nakanishi Hayao, Oda Masahiro, Mori Kensaku, Ito Akihiro, Hasegawa Junichi, Misawa Kazunari, Fuchi Shingo

    MICROMACHINES   Vol. 10 ( 2 )   2019.2

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    DOI: 10.3390/mi10020081

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  149. Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis Reviewed

    Yasuharu Maeda, Shin-eiKudo, Yuichi Mori, Masashi Misawa, Noriyuki Ogata, Seiko Sasanuma, Kunihiko Wakamura, Masahiro Oda, Kensaku Mori, Kazuo Ohtsuka

    GASTROINTESTINAL ENDOSCOPY   Vol. 89 ( 2 ) page: 408 - 415   2019.2

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    DOI: 10.1016/j.gie.2018.09.024

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  150. Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video) Reviewed

    Yasuharu Maeda, Shin-eiKudo, Yuichi Mori, Masashi Misawa, Noriyuki Ogata, Seiko Sasanuma, Kunihiko Wakamura, Masahiro Oda, Kensaku Mori, Kazuo Ohtsuka

    Gastrointestinal endoscopy   Vol. 89 ( 2 ) page: 408-415   2019.2

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  151. Multi-class abdominal organs segmentation with improved V-Nets

    Chen Shen, Fausto Milletari, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    Proceedings of SPIE 10949, Medical Imaging 2019     page: 109490B-1-7   2019.2

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  152. CTからの腹部多臓器抽出におけるgroup normalizationの影響に関する考察

    申 忱, Fausto Milletari, Holger R. Roth, 小田 紘久, 小田 昌宏, 林 雄一郎, 三澤 一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 412 ) page: 143-148   2019.1

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  153. Investigation of extracting the interlobular septa with combination of Hessian analysis and radial structure tensor in micro-CT volume

    Xiaotian Zhao, Hirohisa Oda, Shota Nakamura, Yuichiro Hayashi, Hayato Itoh, Masahiro Oda, Kensaku Mori

    IFMIA 2019     page: 0   2019.1

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  154. 機械学習を用いた腹部動脈血管名自動命名におけるデータ拡張法の適用に関する検討

    鉄村 悠介, 林 雄一郎, 小田 昌宏, 北坂 孝幸, 三澤 一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 412 ) page: 191-196   2019.1

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  155. 敵対的Dense U-netを用いた切除肺マイクロCT像の超解像

    鄭 通, 小田 紘久, Holger R. Roth, 小田 昌宏, 中村 彰太, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 412 ) page: 7-12   2019.1

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  156. 切除肺のマイクロCT像における3D-DBPNを用いた超解像の検討

    鄭 通, 小田 紘久, 小田 昌宏, 守谷 享泰, 中村 彰太, 森 健策

    第11回呼吸機能イメージング研究会学術集会, プログラム抄録集     page: 82   2019.1

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  157. 不均衡データからの特徴選択 超拡大内視鏡画像の病理類型分類に向けて

    伊東 隼人, 森 悠一, 三澤 将史, 小田 昌宏, 工藤 進英, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 412 ) page: 109-114   2019.1

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  158. マルチモーダル画像を用いた深層学習ベースの頭部解剖構造抽出 少量画像データ学習における抽出精度検証

    杉野 貴明, Holger R. Roth, 小田 昌宏, 金 太一, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 412 ) page: 65-70   2019.1

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  159. 経時CT像間の腹部臓器の変形を考慮したリンパ節自動対応付け手法の検討

    舘 高基, 小田 昌宏, 林 雄一郎, 伊東 隼人, 中村 嘉彦, 北坂 孝幸, 三澤 一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 412 ) page: 97-102   2019.1

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  160. Automated Hand Eye Calibration in Laparoscope Holding Robot for Robot Assisted Surgery Reviewed

    Jiang Shuai, Hayashi Yuichiro, Wang Cheng, Oda Masahiro, Kitasaka Takayuki, Misawa Kazunari, Mori Kensaku

    INTERNATIONAL WORKSHOP ON ADVANCED IMAGE TECHNOLOGY (IWAIT) 2019   Vol. 11049   2019

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    DOI: 10.1117/12.2521618

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  161. Applications of Generative Adversarial Networks in Medical Image Processing: Introduction Invited

    ODA Masahiro

    Medical Imaging Technology   Vol. 37 ( 3 ) page: 123-124   2019

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    DOI: 10.11409/mit.37.123

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  162. Weakly-supervised Deep Learning of Interstitial Lung Disease Types on CT Images

    Wang Chenglong, Moriya Takayasu, Hayashi Yuichiro, Roth Holger, Lu Le, Oda Masahiro, Ohkubo Hirotugu, Mori Kensaku

    MEDICAL IMAGING 2019: COMPUTER-AIDED DIAGNOSIS   Vol. 10950   2019

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    DOI: 10.1117/12.2512746

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  163. Artificial Intelligence/Deep Learning for Surgical Assistance Invited

    Oda Masahiro

    Journal of Japan Society of Computer Aided Surgery   Vol. 21 ( 3 ) page: 143-146   2019

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    DOI: 10.5759/jscas.21.143

  164. Radiological and Endoscope Image Analyses in Nagoya University Invited

    ODA Masahiro, SHEN Chen, ODA Hirohisa, MORI Kensaku

    Medical Imaging Technology   Vol. 37 ( 2 ) page: 84-88   2019

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    This paper introduces our medical image analysis researches in the AMED project. Our research topics are radiological and endoscope image analyses. The radiological image analysis includes a blood vessel diagnosis assistance using non-contrasted abdominal CT volumes and an abdominal multi-organ segmentation from CT volumes. The endoscope image analysis includes observing area classifications of endoscope images taken in the stomach and colon. We explain approaches and results of these researches.

    DOI: 10.11409/mit.37.84

  165. Micro-CT in the Analysis of Formalin-Fixed Paraffin-Embedded Blocks of Resected Pancreatic Lesions Reviewed

    Shindo K., Ohuchida K., Roth H. R., Oda H., Iwamoto C., Oda M., Ohtsuka T., Mori K., Hashizume M., Nakamura M.

    PANCREAS   Vol. 48 ( 10 ) page: 1523 - 1523   2019

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  166. Polyp-Size Classification with RGB-D features for Colonoscopy Reviewed

    Itoh Hayato, Roth Holger R., Mori Yuichi, Misawa Masashi, Oda Masahiro, Kudo Shin-ei, Mori Kensaku

    MEDICAL IMAGING 2019: COMPUTER-AIDED DIAGNOSIS   Vol. 10950   2019

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    DOI: 10.1117/12.2513093

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  167. Scanning, registration, and fiber estimation of rabbit hearts using micro-focus and refraction-contrast X-ray CT Reviewed

    Oda Hirohisa, Roth Holger R., Sugino Takaaki, Sunaguchi Naoki, Usami Noriko, Oda Masahiro, Shimao Daisuke, Ichihara Shu, Yuasa Tetsuya, Ando Masami, Akita Toshiaki, Narita Yuji, Mori Kensaku

    MEDICAL IMAGING 2019: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING   Vol. 10953   2019

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    DOI: 10.1117/12.2512145

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  168. Spaciousness Filters for Non-contrast CT Volume Segmentation of the Intestine Region for Emergency Ileus Diagnosis Reviewed

    Oda Hirohisa, Nishio Kohei, Kitasaka Takayuki, Villard Benjamin, Amano Hizuru, Chiba Kosuke, Hinoki Akinari, Uchida Hiroo, Suzuki Kojiro, Itoh Hayato, Oda Masahiro, Mori Kensaku

    MICCAI 2019, Workshop: CLIP2019   Vol. 11840   page: 104-114   2019

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    DOI: 10.1007/978-3-030-32689-0_11

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  169. Tubular Structure Segmentation Using Spatial Fully Connected Network with Radial Distance Loss for 3D Medical Images Reviewed

    Wang Chenglong, Hayashi Yuichiro, Oda Masahiro, Itoh Hayato, Kitasaka Takayuki, Frangi Alejandro F., Mori Kensaku

    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT VI   Vol. 11769   page: 348-356   2019

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    DOI: 10.1007/978-3-030-32226-7_39

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  170. Unsupervised Segmentation of Micro-CT Images Based on a Hybrid of Variational Inference and Adversarial Learning Reviewed

    Moriya Takayasu, Roth Holger R., Nakamura Shota, Oda Hirohisa, Oda Masahiro, Mori Kensaku

    MEDICAL IMAGING 2019: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING   Vol. 10953   2019

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    DOI: 10.1117/12.2513094

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  171. Unsupervised Segmentation of Micro-CT Images of Lung Cancer Specimen Using Deep Generative Models Reviewed

    Moriya Takayasu, Oda Hirohisa, Mitarai Midori, Nakamura Shota, Roth Holger R., Oda Masahiro, Mori Kensaku

    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT VI   Vol. 11769   page: 240-248   2019

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    DOI: 10.1007/978-3-030-32226-7_27

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  172. Visual SLAM for bronchoscope tracking and bronchus reconstruction in bronchoscopic navigation Reviewed

    Wang Cheng, Oda Masahiro, Hayashi Yuichiro, Kitasaka Takayuki, Honma Hirotoshi, Takabatake Hirotsugu, Mori Masaki, Natori Hiroshi, Mori Kensaku

    MEDICAL IMAGING 2019: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING   Vol. 10951   2019

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    DOI: 10.1117/12.2512766

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  173. Discriminative Feature Selection by Optimal Manifold Search for Neoplastic Image Recognition Reviewed

    Itoh Hayato, Mori Yuichi, Misawa Masashi, Oda Masahiro, Kudo Shin-Ei, Mori Kensaku

    COMPUTER VISION - ECCV 2018 WORKSHOPS, PT IV   Vol. 11132   page: 534-549   2019

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    DOI: 10.1007/978-3-030-11018-5_43

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  174. Investigation of extracting interlobular septa with Hessian analysis and Radial Structure Tensor combined with roundness error in micro-CT volume Reviewed

    Zhao Xiaotian, Oda Hirohisa, Nakamura Shota, Hayashi Yuichiro, Itoh Hayato, Oda Masahiro, Mori Kensaku

    INTERNATIONAL FORUM ON MEDICAL IMAGING IN ASIA 2019   Vol. 11050   2019

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    DOI: 10.1117/12.2521646

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  175. Improving V-Nets for multi-class abdominal organ segmentation Reviewed

    Shen Chen, Milletari Fausto, Roth Holger R., Oda Hirohisa, Oda Masahiro, Hayashi Yuichiro, Misawa Kazunari, Mori Kensaku

    MEDICAL IMAGING 2019: IMAGE PROCESSING   Vol. 10949   2019

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    DOI: 10.1117/12.2512790

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  176. ディープラーニング実践の環境構築

    小田 昌宏

    臨床画像   Vol. 35   page: 1120 - 1128   2019

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  177. Development of Colonoscope Tracking Method using Recurrent Neural Network for Colonoscopic Examination Navigation Reviewed

    Masahiro Oda, Holger R. Roth, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Nassir Navab, Kensaku Mori

    Transactions of the Virtual Reality Society of Japan   Vol. 23 ( 4 ) page: 249-252   2018.12

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    DOI: 10.18974/tvrsj.23.4_249

  178. CT 像より自動抽出された動脈領域に対応した機械学習に基づく腹部動脈血管名自動命名法

    鉄村 悠介, 林 雄一郎, 小田 昌宏, 北坂 孝幸, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅶ)-4 ) page: 322-323   2018.11

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  179. Investigation on the condition of using adjacent reconstruction in visual bronchoscope tracking

      Vol. 118 ( 286 ) page: 27-32   2018.11

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  180. 深層学習を用いた屈折 X 線 CT 画像からの眼球構造抽出 ―Sparse annnotation データの学習法に関する検討―

    杉野 貴明, Holger R. Roth, 小田 昌宏, 砂口 尚輝, 島雄 大介, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅲ)-4 ) page: 259-260   2018.11

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  181. 深層学習を用いたマイクロ CT 画像の超解像に関する初期的検討

    鄭 通, Holger R. Roth, 小田 昌宏, 小田 紘久, 中村 彰太, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅱ)-8 ) page: 252-253   2018.11

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  182. 不均衡データセットからの学習データセット構築法 ―機械学習に基づく医用画像分類に向けて―

    伊東 隼人, 森 悠一, 三澤 将史, 小田 昌宏, 工藤 進英, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅲ)-5 ) page: 261-262   2018.11

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  183. ディープラーニングを用いた腹腔鏡映像からの腹腔鏡下胃切除術の手術工程解析の検討

    林 雄一郎, 杉野 貴明, 小田 昌宏, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(ⅩⅠ)-10 ) page: 368-369   2018.11

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  184. イレウス診断支援システムにおける閉塞部位の誤検出修正及び改善ツールの構築

    西尾 光平, 小田 紘久, 千馬 耕亮, 北坂 孝幸, Holger R. Roth, 伊東 隼人, 林 雄一郎, 小田 昌宏, 檜 顕成, 内田 広夫, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅹ)-3 ) page: 348-349   2018.11

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  185. U‒Net を用いた腹腔鏡動画像における出血領域検出に関する検討

    小澤 卓也, 小田 紘久, 伊東 隼人, 北坂 孝幸, Holger R. Roth, 小田 昌宏, 林 雄一郎, 三澤 一成, 伊藤 雅昭, 竹下 修由, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(6)-10 ) page: 370   2018.11

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  186. SLAM ベースのビジュアルトラッキングにおける隣接フレーム利用再構成手法の評価

    王 成, 小田 昌宏, 林 雄一郎, 北坂 孝幸, 本間 裕敏, 高畠 博嗣, 森 雅樹, 名取 博, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅸ)-4 ) page: 342-343   2018.11

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  187. Micro CT and Histopathological Image Registration Based on Deep-Learning Assisted Image Registration

    Kensaku Mori, Kai Nagara, Shota Nakamura, Hirohisa Oda, MENG, Holger R. Roth, Masahiro Oda

    RSNA2018     page: CH218-ED-X   2018.11

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  188. 生成モデルを利用したマイクロ CT 画像の半教師ありセグメンテーション

    守谷 享泰, Holger R. Roth, 中村 彰太, 小田 紘久, 小田 昌宏, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅵ)-9 ) page: 312-313   2018.11

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  189. 腹腔鏡把持ロボットのための自動ハンドアイキャリブレーションの検討

    蒋 帥, 林 雄一郎, 小田 昌宏, 北坂 孝幸, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第27回日本コンピュータ外科学会大会特集号   Vol. 20 ( 4 18(Ⅹ)-10 ) page: 359   2018.11

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  190. Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy A Prospective Study Reviewed

    Yuichi Mori, Shin-ei Kudo, Masashi Misawa, Yutaka Saito, Hiroaki Ikematsu, Kinichi Hotta, Kazuo Ohtsuka, Fumihiko Urushibara, Shinichi Kataoka, Yushi Ogawa, Yasuharu Maeda, Kenichi Takeda, Hiroki Nakamura, Katsuro Ichimasa, Toyoki Kudo, Takemasa Hayashi, Kunihiko Wakamura, Fumio Ishida, Haruhiro Inoue, Hayato Itoh, Masahiro Oda, Kensaku Mori

    ANNALS OF INTERNAL MEDICINE   Vol. 169 ( 6 ) page: 357 - 366   2018.9

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    DOI: 10.7326/M18-0249

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  191. Layout of alveoli and pores of Kohn on magnified 3D printed model of the peripheral lung specimen by micro CT Reviewed

    Natori Hiroshi, Takabatake Hirotsugu, Mori Masaki, Mori Kensaku, Oda Masahiro, Koba Hiroyuki, Takahashi Hiroki

    EUROPEAN RESPIRATORY JOURNAL   Vol. 52   2018.9

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    DOI: 10.1183/13993003.congress-2018.PA860

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  192. Application of three-dimensional print in minor hepatectomy following liver partition between anterior and posterior sectors Reviewed

    Tsuyoshi Igami, Yoshihiko Nakamura, Masahiro Oda, Hiroshi Tanaka, Motoi Nojiri, Tomoki Ebata, Yukihiro Yokoyama, Gen Sugawara, Takashi Mizuno, Junpei Yamaguchi, Kensaku Mori, Masato Nagino

    ANZ JOURNAL OF SURGERY   Vol. 88 ( 9 ) page: 882 - 885   2018.9

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    DOI: 10.1111/ans.14331

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  193. Sparse annotationによる深層学習ベースの解剖構造抽出:屈折X線CT像からの精密な眼球セグメンテーション

    杉野貴明, Holger R. Roth, 小田昌宏, 砂口尚輝, 島雄大介, 市原周, 湯浅哲也, 安藤正海, 森健策

    MIRU2018     page: PS3-11   2018.8

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  194. 超拡大内視鏡における病理画像分類のための特徴選択法

    伊東 隼人, 森 悠一, 三澤 将史, 小田 昌宏, 工藤 進英, 森 健策

    MIRU2018     page: PS2-17   2018.8

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  195. Fast Marching Algorithmに基づく小児CT像からの腸管閉塞部位検出手法

    西尾 光平, 小田 紘久, 千馬 耕亮, 北坂 孝幸, Holger Roth, 伊東 隼人, 小田 昌宏, 檜 顕成, 内田 広夫, 森 健策

    第37回日本医用画像工学会大会予稿集     page: OP1-6   2018.7

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  196. ウサギ心臓の屈折CT像における線維配向の可視化ならびに評価

    小田 紘久, Holger R. Roth, 砂口 尚輝, 宇佐美 紀子, 小田 昌宏, 島雄 大介, 市原 周, 湯浅 哲也, 安藤 正海, 秋田 利明, 成田 裕司, 森 健策

    第37回日本医用画像工学会大会予稿集     page: OP1-8   2018.7

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  197. 機械学習を用いた腹部動脈血管名自動命名における臓器情報および多血管相互関係利用方法の検討

    鉄村 悠介, Holger Roth, 林 雄一郎, 小田 昌宏, 三澤 一成, 森 健策

    第37回日本医用画像工学会大会予稿集     page: OP14-2   2018.7

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  198. 機械学習による内視鏡動画インスタンスセグメンテーションのための手動アノテーションツールの開発

    小澤 卓也, 小田 紘久, 伊東 隼人, 北坂 孝幸, Holger R. Roth, 小田 昌宏, 林 雄一郎, 三澤 一成, 伊藤 雅昭, 竹下 修由, 森 健

    第37回日本医用画像工学会大会予稿集     page: OP1-7   2018.7

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  199. 教師なし深度推定を利用したRGB-D 特徴抽出に基づくポリープのトリナリサイズ推定

    伊東隼人, Holger Roth, 三澤将史, 森悠一, 小田昌宏, 工藤進英, 森健策

    第37回日本医用画像工学会大会予稿集     page: OP14-4   2018.7

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  200. マイクロCT画像からのRSTを用いた小葉壁抽出手法の検討

    趙 笑添, Holger R. Roth, 中村彰太, 小田紘久, 林 雄一郎, 守谷享泰, 長柄 快, 小田昌宏, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 150 ) page: 11-16   2018.7

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  201. 胃の変形情報を利用した経時リンパ節の自動対応付け手法の精度向上に関する研究

    舘 高基, 小田 昌宏, 林 雄一郎, 中村 嘉彦, 北坂 孝幸, 三澤 一成, 森 健策

    第37回日本医用画像工学会大会予稿集     page: OP4-2   2018.7

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  202. 隣接復元を用いたSLAMベースの気管支鏡追跡の改善

    王 成, 小田 昌宏, 林 雄一郎, 本間 裕敏, 高畑 博嗣, 森 雅樹, 名取 博, 森 健策

    第37回日本医用画像工学会大会予稿集     page: OP13-6   2018.7

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  203. Micro-focus X-ray CT of the heart:A comparison with X-ray refraction-contrast CT,

    Hirohisa Oda, Holger R. Roth, Naoki Sunaguchi, Daisuke Shimao, Takaaki Sugino, Masahiro Oda, Toshiaki Akita, Yuji Narita, Shu Ichihara, Tetsuya Yuasa, Masami Ando, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s140-142   2018.6

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  204. Polyp detection in colonoscopic videos by using spatio-temporal feature

    Hayato Itoh, Holger R. Roth, Masashi Misawa, Yuichi Mori, Masahiro Oda, Shin-ei Kudo, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s97-98   2018.6

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  205. Automated ganglion cell detection using fully convolutional networks and evaluation under different training losses

    Hirohisa Oda, Kosuke Chiba, Holger R. Roth, Takayuki Kitasaka, Masahiro Oda, Akinari Hinoki, Hiroo Uchida, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s104-106   2018.6

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  206. Improvement of robustness of SLAM-based bronchoscope tracking by posture guided feature matching

    Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s11-12   2018.6

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  207. Evaluation of 3D fully convolutional networks for multi-class organ segmentation in contrast-enhanced CT

    Chen Shen, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Tadaaki Miyamoto, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s21-22   2018.6

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  208. Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience Reviewed

    Misawa Masashi, Kudo Shin-ei, Mori Yuichi, Cho Tomonari, Kataoka Shinichi, Yamauchi Akihiro, Ogawa Yushi, Maeda Yasuharu, Takeda Kenichi, Ichimasa Katsuro, Nakamura Hiroki, Yagawa Yusuke, Toyoshima Naoya, Ogata Noriyuki, Kudo Toyoki, Hisayuki Tomokazu, Hayashi Takemasa, Wakamura Kunihiko, Baba Toshiyuki, Ishida Fumio, Itoh Hayato, Roth Holger, Oda Masahiro, Mori Kensaku

    GASTROENTEROLOGY   Vol. 154 ( 8 ) page: 2027 - +   2018.6

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    DOI: 10.1053/j.gastro.2018.04.003

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  209. DIAGNOSTIC IMAGING SYSTEM WITH VIRTUAL ENTEROSCOPY AND COMPUTER-AIDED DETECTION FOR EVALUATION OF SMALL BOWEL LESIONS OF CROHN'S DISEASE Reviewed

    Furukawa Kazuhiro, Miyahara Ryoji, Funasaka Kohei, Suhara Hiroki, Matsushita Masanobu, Yamamura Takeshi, Ishikawa Takuya, Ohno Eizaburo, Nakamura Masanao, Kawashima Hiroki, Watanabe Osamu, Oda Masahiro, Mori Kensaku, Hirooka Yoshiki, Goto Hidemi

    GASTROINTESTINAL ENDOSCOPY   Vol. 87 ( 6 ) page: AB304-AB304   2018.6

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  210. An application of cascaded 3D fully convolutional networks for medical image segmentation Reviewed

    Holger R. Roth, Hirohisa Oda, Xiangrong Zhou, Natsuki Shimizu, Ying Yang, Yuichiro Hayashi, Masahiro Oda, Michitaka Fujiwara, Kazunari Misawa, Kensaku Mori

    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS   Vol. 66   page: 90 - 99   2018.6

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    DOI: 10.1016/j.compmedimag.2018.03.001

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  211. DIAGNOSTIC IMAGING SYSTEM WITH VIRTUAL ENTEROSCOPY AND COMPUTER-AIDED DETECTION FOR EVALUATION OF SMALL BOWEL LESIONS OF CROHN'S DISEASE Reviewed

    Furukawa Kazuhiro, Miyahara Ryoji, Funasaka Kohei, Suhara Hiroki, Matsushita Masanobu, Yamamura Takeshi, Ishikawa Takuya, Ohno Eizaburo, Nakamura Masanao, Kawashima Hiroki, Watanabe Osamu, Oda Masahiro, Mori Kensaku, Hirooka Yoshiki, Goto Hidemi

    GASTROINTESTINAL ENDOSCOPY   Vol. 87 ( 6 ) page: AB304-AB304   2018.6

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  212. 3D U-Netと測地距離カーネルを取り入れた全連結条件付き確率場に基づく医用画像からの多臓器自動抽出

    楊 瀛, Roth Holger, 小田昌宏, 北坂孝幸, 三澤一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 117 ( 518 ) page: 75-80   2018.3

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  213. CNNによる回帰を用いた臓器領域の位置推定手法の初期的検討

    清水南月, 小田昌宏, ロス ホルガー, 林 雄一郎, 三澤一成, 藤原道隆, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 117 ( 518 ) page: 81-86   2018.3

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  214. Pre/intra-operative diagnosis and navigational assistance based on multidisciplinary computational anatomy

    Kensaku Mori, Masahiro Oda, Holger R roth, Yoshihiko Nakamura, Yoshito Mekada, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kazuhiro Durukawa, Shu Ichihara

        page: 87-105   2018.3

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  215. ディープラーニングを用いた教師なし学習によるレジストレーション手法の初期的検討

    長柄 快, Holger R. Roth, 中村彰太, 小田昌宏, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 117 ( 518 ) page: 7-12   2018.3

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  216. 複数のステレオ内視鏡画像からの臓器形状復元の定量評価

    柴田睦実, 林 雄一郎, 小田昌宏, 三澤一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 117 ( 518 ) page: 117-122   2018.3

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  217. 超拡大内視鏡画像における腫瘍性ポリープ分類に向けたグラスマン距離に基づく特徴選択法

    伊東隼人, 森 悠一, 三澤将史, 小田昌宏, 工藤進英, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 117 ( 518 ) page: 51-56   2018.3

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  218. Develop and Validate a Finite Element Method Model for Deformation Matching of Laparoscopic Gastrectomy Navigation Reviewed

    Chen Tao, Wei Guodong, Shi Weili, Hayashi Yuichiro, Oda Masahiro, Jiang Zhengang, Li Guoxin, Mori Kensaku

    MEDICAL IMAGING 2018: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING   Vol. 10576   2018

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    DOI: 10.1117/12.2293288

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  219. Micro Anatomical Structure Imaging by Desktop Micro-focus X-ray CT Scanner Invited

    MORI Kensaku, NAKAMURA Shota, AKITA Toshiaki, ODA Hirohisa, Holger ROTH R., ODA Masahiro

    Medical Imaging Technology   Vol. 36 ( 3 ) page: 127-132   2018

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    This paper shows examples of micro anatomical structure imaging using a desktop micro-focus X-ray CT scanner. Currently clinical X-ray CT scanners can take CT images in 0.5mm to 1mm per voxel in resolution. Such scanner can take anatomical structures close to image resolution of scanners. Micro-focus X-ray CT (micro CT) scanner can take CT images of 1&mu;m per voxel to 50&mu;m per voxel in resolution. Such scanner enables us to explore micro anatomical structures. This paper shows several examples of micro CT images of lung and heart specimens with discussion on future direction.

    DOI: 10.11409/mit.36.127

  220. Airway Segmentation from 3D Chest CT Volumes Based on Volume of Interest Using Gradient Vector Flow

    MENG Qier, KITASAKA Takayuki, ODA Masahiro, UENO Junji, MORI Kensaku

    Medical Imaging Technology   Vol. 36 ( 3 ) page: 133-146   2018

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    In this paper, we propose a new airway segmentation algorithm from 3D chest CT volumes based on the volume of interest (VOI). The algorithm segments each bronchial branch by recognizing the airway regions from the trachea using the VOIs to segment each branch. A VOI is placed to envelop the branch currently being processed. Then a cavity enhancement filter is performed only inside the current VOI so that each branch is extracted. At the same time, we perform a leakage detection scheme to avoid any leakage regions inside the VOI. Next the gradient vector flow magnitude map and a tubular-likeness function are computed in each VOI. This assists the predictions of both the position and direction of the next child VOIs to detect the next child branches to continue the tracking algorithm. Finally, we unify all of the extracted airway regions to form a complete airway tree. We used a dataset that includes 50 standard-dose human chest CT volumes to evaluate our proposed algorithm. The average extraction rate was approximately 78.1% with a significantly decreased false positive rate compared to the previous method.

    DOI: 10.11409/mit.36.133

  221. A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multi-organ Segmentation Reviewed

    Roth Holger R., Shen Chen, Oda Hirohisa, Sugino Takaaki, Oda Masahiro, Hayashi Yuichiro, Misawa Kazunari, Mori Kensaku

    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT IV   Vol. 11073   page: 417 - 425   2018

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    DOI: 10.1007/978-3-030-00937-3_48

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  222. Guidance of Deep Learning for Medical Image Processing: Introduction Invited

    ODA Masahiro

    Medical Imaging Technology   Vol. 36 ( 2 ) page: 45 - 46   2018

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    DOI: 10.11409/mit.36.45

  223. Towards Automated Colonoscopy Diagnosis: Binary Polyp Size Estimation via Unsupervised Depth Learning Reviewed

    Itoh Hayato, Roth Holger R., Lu Le, Oda Masahiro, Misawa Masashi, Mori Yuichi, Kudo Shin-ei, Mori Kensaku

    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II   Vol. 11071   page: 611 - 619   2018

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    DOI: 10.1007/978-3-030-00934-2_68

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  224. Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

    Roth Holger, Oda Masahiro, Shimizu Natsuki, Oda Hirohisa, Hayashi Yuichiro, Kitasaka Takayuki, Fujiwara Michitaka, Misawa Kazunari, Mori Kensaku

    MEDICAL IMAGING 2018: IMAGE PROCESSING   Vol. 10574   2018

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    DOI: 10.1117/12.2293499

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  225. Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means Reviewed

    Moriya Takayasu, Roth Holger H., Nakamura Shota, Oda Hirohisa, Nagara Kai, Oda Masahiro, Mori Kensaku

    MEDICAL IMAGING 2018: DIGITAL PATHOLOGY   Vol. 10581   2018

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    DOI: 10.1117/12.2292172

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  226. Unsupervised Segmentation of 3D Medical Images Based on Clustering and Deep Representation Learning Reviewed

    Moriya Takayasu, Roth Holger R., Nakamura Shota, Oda Hirohisa, Nagara Kai, Oda Masahiro, Mori Kensaku

    MEDICAL IMAGING 2018: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING   Vol. 10578   2018

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    DOI: 10.1117/12.2293414

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  227. Important Points to Take Advantage of Deep Learning Invited

    ODA Masahiro

    Medical Imaging Technology   Vol. 36 ( 2 ) page: 72-75   2018

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    Deep learning can be applied to many tasks in medical image processing. There are some points to be careful in research use of deep learning to take advantage of its performance. Among such points, three topics including manual specification of many parameters in deep learning, pitfalls of data augmentation, and how randomly selected parameters in deep learning affect its performance, are discussed here.

    DOI: 10.11409/mit.36.72

  228. Automatic segmentation of eyeball structures from micro-CT images based on sparse annotation Reviewed

    Sugino Takaaki, Roth Holger R., Oda Masahiro, Omata Seiji, Sakuma Shinya, Arai Fumihito, Mori Kensaku

    MEDICAL IMAGING 2018: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING   Vol. 10578   2018

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    DOI: 10.1117/12.2293431

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  229. Fully Convolutional Network-Based Eyeball Segmentation from Sparse Annotation for Eye Surgery Simulation Model Reviewed

    Sugino Takaaki, Roth Holger R., Oda Masahiro, Mori Kensaku

    International Workshop on Bio-Imaging and Visualization for Patient-Customized Simulations, BIVPCS 2018   Vol. 11042   page: 118-126   2018

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    DOI: 10.1007/978-3-030-01045-4_14

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  230. Fine Segmentation of Tiny Blood Vessel Based on Fully-Connected Conditional Random Field Reviewed

    Wang Chenglong, Oda Masahiro, Yoshino Yasushi, Yamamoto Tokunori, Mori Kensaku

    MEDICAL IMAGING 2018: IMAGE PROCESSING   Vol. 10574   2018

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    DOI: 10.1117/12.2293486

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  231. Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT images Reviewed

    Oda Hirohisa, Roth Holger R., Bhatia Kanwal K., Oda Masahiro, Kitasaka Takayuki, Iwano Shingo, Homma Hirotoshi, Takabatake Hirotsugu, Mori Masaki, Natori Hiroshi, Schnabel Julia A., Mori Kensaku

    MEDICAL IMAGING 2018: COMPUTER-AIDED DIAGNOSIS   Vol. 10575   2018

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    DOI: 10.1117/12.2287066

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  232. Deep Learning and Its Application to Medical Image Segmentation Invited

    ROTH Holger R., SHEN Chen, ODA Hirohisa, ODA Masahiro, HAYASHI Yuichiro, MISAWA Kazunari, MORI Kensaku

    Medical Imaging Technology   Vol. 36 ( 2 ) page: 63-71   2018

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    One of the most common tasks in medical imaging is semantic segmentation. Achieving this segmentation automatically has been an active area of research, but the task has been proven very challenging due to the large variation of anatomy across different patients. However, recent advances in deep learning have made it possible to significantly improve the performance of image recognition and semantic segmentation methods in the field of computer vision. Due to the data driven approaches of hierarchical feature learning in deep learning frameworks, these advances can be translated to medical images without much difficulty. Several variations of deep convolutional neural networks have been successfully applied to medical images. Especially fully convolutional architectures have been proven efficient for segmentation of 3D medical images. In this article, we describe how to build a 3D fully convolutional network (FCN) that can process 3D images in order to produce automatic semantic segmentations. The model is trained and evaluated on a clinical computed tomography (CT) dataset and shows stateof-the-art performance in multi-organ segmentation.

    DOI: 10.11409/mit.36.63

  233. Cascade classification of endocytoscopic images of colorectal lesions for automated pathological diagnosis Reviewed

    Itoh Hayato, Mori Yuichi, Misawa Masashi, Oda Masahiro, Kudo Shin-ei, Mori Kensaku

    MEDICAL IMAGING 2018: COMPUTER-AIDED DIAGNOSIS   Vol. 10575   2018

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    DOI: 10.1117/12.2293495

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  234. BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images Reviewed

    Oda Hirohisa, Roth Holger R., Chiba Kosuke, Sokolic Jure, Kitasaka Takayuki, Oda Masahiro, Hinoki Akinari, Uchida Hiroo, Schnabel Julia A., Mori Kensaku

    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II   Vol. 11071   page: 228-236   2018

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    DOI: 10.1007/978-3-030-00934-2_26

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  235. Machine learning-based colon deformation estimation method for colonoscope tracking Reviewed

    Oda Masahiro, Kitasaka Takayuki, Furukawa Kazuhiro, Miyahara Ryoji, Hirooka Yoshiki, Goto Hidemi, Navab Nassir, Mori Kensaku

    MEDICAL IMAGING 2018: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING   Vol. 10576   2018

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    DOI: 10.1117/12.2293936

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  236. Development of a CNC abrasive machining technique for 3D-printed organ models by utilizing a flexible mechanical structure

    OHBA Takayuki, SUZUKI Norikazu, SHAMOTO Eiji, ODA Masahiro, MORI Kensaku, TAKEUCHI Yoshimi

    The Proceedings of The Manufacturing & Machine Tool Conference   Vol. 2018.12 ( 0 ) page: C20   2018

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    This paper presents a novel surface finishing technology for free-formed surfaces of three-dimensional (3D) printed resin organ models. Demand for the medical applications of three-dimensional layered fabrication technology such as organ models is increasing. Surface integrity deteriorations due to laminated micro steps formed on the surface is a significant problem. In general, material removal of layered micro step is performed manually, hence automation technology is desired. In the present study, we proposed a quasi-constant machining force grinding / polishing by use of 3-axis CNC machine tools. The workpiece is fixed to the flexible mechanical structure, whose translational flexibilities are designed to be identical regardless of contact directions and low spring rigidity. With the developed machining system, the liver model processing was demonstrated. Experimental results verified the feasibility of highly-efficient abrasive machining.

    DOI: 10.1299/jsmemmt.2018.12.c20

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  237. On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks

    Chen Shen, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    MI2017-51   Vol. 117 ( 281 ) page: 15-20   2017.11

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  238. Study on the Robustness of ORB-SLAM Based Outlier Elimination in Bronchoscope Tracking -- RANSAC + EPnP for Outlier Detection --

    Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    MI2017-58   Vol. 117 ( 281 ) page: 47-52   2017.11

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  239. Automated Multi-Organ Segmentation in Abdominal CT with Hierarchical 3D Fully-Convolutional Networks

    Holger R. Roth, Hirohisa Oda, MENG, Yuichiro Hayashi, Masahiro Oda, Natsuki Shimizu, Kensaku Mori, Michitaka Fujiwara, Kazunari Misawa

    RSNA 2017 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 267   2017.11

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  240. Automated mediastinal lymph node detection from CT volumes based on intensity targeted radial structure tensor analysis Reviewed International coauthorship

    Hirohisa Oda, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia A. Schnabel, Kensaku Mori

    JOURNAL OF MEDICAL IMAGING   Vol. 4 ( 4 ) page: 044502   2017.10

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    DOI: 10.1117/1.JMI.4.4.044502

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  241. 3D Fully Convolutional Networks と全連結条件付確率場による 3 次元 CT 画像からの多臓器自動抽出に関する検討

    楊 瀛, 小田昌宏, Roth Holger, 北坂孝幸, 三澤一成, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 268-269   2017.10

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  242. μCT 画像を用いた大変形を含む連続切片 HE 染色画像の 3 次元再構築

    長柄 快, Holger Roth, 中村彰太, 小田紘久, 守谷享泰, 小田昌宏, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 363-364   2017.10

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  243. 深層学習を用いたマイクロ CT 画像からの眼球構造自動抽出 〜少量データ学習による解剖構造抽出性能の検証

    杉野貴明, Holger R. Roth, 小田昌宏, 小俣誠二, 佐久間臣耶, 新井史人, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 241-242   2017.10

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  244. 気管支鏡追跡における ORB-SLAM 適用に関する初期的検討

    王 成, 小田昌宏, 林 雄一郎, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 324-325   2017.10

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  245. 機械学習を用いた腹部動脈血管名自動命名における臓器情報利用方法に関する一考察

    鉄村悠介, Holger Roth, 林 雄一郎, 小田昌宏, 進藤幸治, 大内田研宙, 橋爪 誠, 三澤一成, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 361-362   2017.10

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  246. レベルセット法を用いた腎臓皮質と髄質領域の分割

    王 成龍, 小田昌宏, 永山 洵, 吉野 能, 山本徳則, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 266-267   2017.10

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  247. マイクロ CT を用いた膵臓パラフィンブロック標本の解析

    進藤幸治, 大内田研宙, Holger R. Roth, 小田紘久, 岩本千佳, 小田昌宏, 中村雅史, 森 健策, 橋爪 誠

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 244-245   2017.10

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  248. サポートベクタマシンを用いたラジオミクスベースの消化管間質性腫瘍リスク評価システム

    陳 韜, 小田紘久, Holger R. Roth, 北坂孝幸, 小田昌宏, 李 国新, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 239-240   2017.10

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  249. 自動設計特徴量を用いた 3 次元腹部 CT 像における膵臓領域の位置推定

    清水南月, Holger R. Roth, 小田昌宏, 三澤一成, 藤原道隆, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 270-271   2017.10

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  250. 超拡大大腸内視鏡画像を利用した病理自動診断 〜腫瘍性病変に関する分類精度解析〜

    伊東隼人, 森 悠一, 三澤将史, 小田昌宏, 工藤進英, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 319-320   2017.10

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  251. 複数フレームのステレオ内視鏡画像を用いた臓器表面形状復元に関する検討

    柴田睦実, 林 雄一郎, 小田昌宏, 三澤一成, 森 健策

    日本コンピュータ外科学会誌 第26回日本コンピュータ外科学会大会特集号   Vol. 19 ( 4 ) page: 326-327   2017.10

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  252. Virtual 3D microscope and magnified 3D print for naked eye analyses of alveoli and alveolar duct structures by Heitzman lung specimen with micro CT

    Hiroshi Natori, Masaki Mori, Hirotsugu Takabatake, Hirotoshi Homma, ensaku Mori, Masahiro Oda, Hiroyuki Koba, Hiroki Takahashi

    ERS International congress 2017     page: Session 439   2017.9

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  253. Accuracy of diagnosing invasive colorectal cancer using computer-aided endocytoscopy Reviewed

    Kenichi Takeda, Shin-ei Kudo, Yuichi Mori, Masashi Misawa, Toyoki Kudo, Kunihiko Wakamura, Atsushi Katagiri, Toshiyuki Baba, Eiji Hidaka, Fumio Ishida, Haruhiro Inoue, Masahiro Oda, Kensaku Mori

    ENDOSCOPY   Vol. 49 ( 8 ) page: 798 - 802   2017.8

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    DOI: 10.1055/s-0043-105486

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  254. Multi-atlas pancreas segmentation: Atlas selection based on vessel structure Reviewed International coauthorship

    Ken'ichi Karasawa, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Chengwen Chu, Guoyan Zheng, Daniel Rueckert, Kensaku Mori

    MEDICAL IMAGE ANALYSIS   Vol. 39   page: 18 - 28   2017.7

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    DOI: 10.1016/j.media.2017.03.006

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  255. K-means法とJoint Unsupervised Learningによる3次元医用画像の教師なしセグメンテーション(Unsupervised 3D Medical Image Segmentation using K-means and Joint Unsupervised Learning) Reviewed

    守谷 享泰, Roth Holger R., 中村 彰太, 小田 紘久, 長柄 快, 小田 昌宏, 森 健策

    日本医用画像工学会大会予稿集   Vol. 36回   page: 546 - 548   2017.7

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    本論文では,3次元医用画像向けの新しい教師なしセグメンテーションの手法を提案する.提案手法は2つの段階に分けられる.1つ目の段階では,JULEを用いた深層表現学習をおこなう.JULEは,CNNから出力される表現のクラスタリングと,クラスタラベルを教師信号としたCNNの更新を繰り返す手法である.2つ目の段階では,訓練済みのCNNから生成された深層表現に対し,K-means法を適用してセグメンテーションをおこなう.評価には肺がん標本のマイクロCT画像を用い,浸潤領域,非浸潤領域,正常領域という3つの領域に分けることを試みた.マイクロCT画像上で病理組織学的特徴に基づいたセグメンテーションをおこなうことは,将来の病理診断精度の向上につながる.セグメンテーション結果の定性評価から,深層表現が3次元医用画像のセグメンテーションに有用であることが示された.(著者抄録)

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  256. 3DU-Netによる3次元胸部CT像からのリンパ節検出

    小田 紘久, KanwalK.Bhatia, HolgerR.Roth, 小田 昌宏, 北坂 孝幸, 岩野 信吾, 本間 裕敏, 高畠 博嗣, 森 雅樹, 名取 博, JuliaA.Schnabel, 森 健策

    第36回日本医用画像工学会大会予稿集     page: OP1-6   2017.7

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  257. Improvement on Robustness of ORB-SLAM Based Surgical Navigation System by Building Submap

    王成, 小田昌宏, 林雄一郎, 三澤一成, 森健策

    第36回日本医用画像工学会大会予稿集     page: OP2-6   2017.7

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  258. 機械学習を用いた腹部動脈血管名自動命名における肝動脈分岐情報利用方法に関する一考察

    鉄村 悠介, 張 暁楠, Holger Roth, 林 雄一郎, 小田 昌宏, 三澤 一成, 森 健策

    第36回日本医用画像工学会大会予稿集     page: OP6-1   2017.7

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  259. 条件付き確率場による医用画像からの多臓器抽出におけるHigher Order Potential とボクセル連結構造の影響に関する考察

    楊瀛, 小田昌宏, Roth Holger, 北坂孝幸, 三澤一成, 森健策

    第36回日本医用画像工学会大会予稿集     page: OP16-4   2017.7

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  260. マイクロ CT 画像情報を利用した特徴点対応付けに基づく顕微鏡画像の 3 次元再構築

    長柄 快, Holger R. ROTH, 中村 彰太, 小田 紘久, 守谷 享泰, 小田 昌宏, 森 健策

    第36回日本医用画像工学会大会予稿集     page: OP14-1   2017.7

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  261. ステレオ内視鏡画像からの臓器形状復元手法における複数フレームの利用に関する初期的検討

    柴田 睦実, 林 雄一郎, 小田 昌宏, 三澤 一成, 森 健策

    第36回日本医用画像工学会大会予稿集     page: OP2-8   2017.7

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  262. Torso organ segmentation in CT using fine-tuned 3D fully convolutional networks

    Holger ROTH, Ying YANG, Masahiro ODA, Hirohisa ODA, Yuichiro HAYASHI, Natsuki SHIMIZU, Takayuki KITASAKA, Michitaka FUJIWARA, Kazunari MISAWA, Kensaku MORI

        page: OP1-8   2017.7

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  263. K-means 法と Joint Unsupervised Learning による3次元医用画像の教師なしセグメンテーション

    守谷享泰, Holger R. Roth, 中村彰太, 小田紘久, 長柄快, 小田昌宏, 森健策

    第36回日本医用画像工学会大会予稿集     page: OP16-5   2017.7

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  264. 血管情報を用いた経時リンパ節の自動対応付け手法に関する研究

    舘 高基, 小田 昌宏, 中村 嘉彦, 寶珠山 裕, 三澤 一成, 森 健策

    第36回日本医用画像工学会大会予稿集     page: OP15-4   2017.7

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  265. Feature-based registration of micro CT volumes

    Kai Nagara, Shota Nakamura, Hoiger R. Roth, Masahiro Oda, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kesaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 12   page: S201-S203   2017.6

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  266. Multi-organ segmentation in abdominal CT using 3D fully convolutional networks

    Holger R. Roth, Masahiro Oda, Yuichiro Hayashi, Hirohisa Oda, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 12   page: S55-S57   2017.6

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  267. Automatic anatomical labeling of arteries and veins using conditional random fields Reviewed

    Takayuki Kitasaka, Mitsuru Kagajo, Yukitaka Nimura, Yuichiro Hayashi, Masahiro Oda, Kazunari Misawa, Kensaku Mori

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 12 ( 6 ) page: 1041 - 1048   2017.6

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    DOI: 10.1007/s11548-017-1549-x

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  268. Accuracy of computer-aided diagnosis based on narrow-band imaging endocytoscopy for diagnosing colorectal lesions: comparison with experts Reviewed

    Masashi Misawa, Shin-ei Kudo, Yuichi Mori, Kenichi Takeda, Yasuharu Maeda, Shinichi Kataoka, Hiroki Nakamura, Toyoki Kudo, Kunihiko Wakamura, Takemasa Hayashi, Atsushi Katagiri, Toshiyuki Baba, Fumio Ishida, Haruhiro Inoue, Yukitaka Nimura, Masahiro Oda, Kensaku Mori

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 12 ( 5 ) page: 757-766   2017.6

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    DOI: 10.1007/s11548-017-1542-4

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  269. Diagnostic Ability of Automated Diagnosis System Using Endocytoscopy for Invasive Colorectal Cancer Reviewed

    Takeda Kenichi, Kudo Shinei, Mori Yuichi, Kataoka Shinichi, Yasuharu Maeda, Ogawa Yushi, Nakamura Hiroki, Misawa Masashi, Kudo Toyoki, Wakamura Kunihiko, Hayashi Takemasa, Katagiri Atsushi, Baba Toshiyuki, Hidaka Eiji, Ishida Fumio, Inoue Haruhiro, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 85 ( 5 ) page: AB408-AB408   2017.5

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  270. Artificial Intelligence for Endocytoscopy Provides Fully Automated Diagnosis of Histological Remission in Ulcerativ E. Coli Tis Reviewed

    Yasuharu Maeda, Kudo Shinei, Mori Yuichi, Misawa Masashi, Wakamura Kunihiko, Hayashi Seiko, Ogata Noriyuki, Takeda Kenichi, Kudo Toyoki, Hayashi Takemasa, Katagiri Atsushi, Ishida Fumio, Ohtsuka Kazuo, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 85 ( 5 ) page: AB248-AB248   2017.5

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  271. Computer-Aided Diagnosis Based on Endocytoscopy With Narrow-Band Imaging Allows Accurate Diagnosis of Diminutive Colorectal Lesions Reviewed

    Misawa Masashi, Kudo Shinei, Mori Yuichi, Takeda Kenichi, Kataoka Shinichi, Nakamura Hiroki, Maeda Yasuharu, Ogawa Yushi, Yamauchi Akihiro, Igarashi Kenta, Hayashi Takemasa, Kudo Toyoki, Wakamura Kunihiko, Katagiri Atsushi, Baba Toshiyuki, Ishida Fumio, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 85 ( 5 ) page: AB57-AB57   2017.5

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  272. Can Artificial Intelligence Correctly Diagnose Sessile Serrated Adenomas/Polyps? Reviewed

    Mori Yuichi, Kudo Shinei, Ogawa Yushi, Misawa Masashi, Takeda Kenichi, Kudo Toyoki, Wakamura Kunihiko, Hayashi Takemasa, Ichimasa Katsuro, Maeda Yasuharu, Toyoshima Naoya, Nakamura Hiroki, Katagiri Atsushi, Baba Toshiyuki, Ishida Fumio, Oda Masahiro, Mori Kensaku, Inoue Haruhiro

    GASTROINTESTINAL ENDOSCOPY   Vol. 85 ( 5 ) page: AB510-AB510   2017.5

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  273. Diagnostic Ability of Automated Diagnosis System Using Endocytoscopy for Invasive Colorectal Cancer Reviewed

    Takeda Kenichi, Kudo Shinei, Mori Yuichi, Kataoka Shinichi, Yasuharu Maeda, Ogawa Yushi, Nakamura Hiroki, Misawa Masashi, Kudo Toyoki, Wakamura Kunihiko, Hayashi Takemasa, Katagiri Atsushi, Baba Toshiyuki, Hidaka Eiji, Ishida Fumio, Inoue Haruhiro, Oda Masahiro, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 85 ( 5 ) page: AB408-AB408   2017.5

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  274. Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume Reviewed

    Qier Meng, Takayuki Kitasaka, Yukitaka Nimura, Masahiro Oda, Junji Ueno, Kensaku Mori

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 12 ( 2 ) page: 245 - 261   2017.2

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    DOI: 10.1007/s11548-016-1492-2

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  275. GPU Implementation of SLIC Supervoxel Oversegmentation

    Hirohisa Oda, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Julia A. Schnabel, Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 266-268   2017.1

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  276. Multi-scale Image Fusion Between Pre-operative Clinical CT and X-ray microtomography of Lung Pathology

    Holger Roth, Kai Nagara, Hirohisa Oda, Masahiro Oda, Tomoshi Sugiyama, Shota Nakamura, Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 54-56   2017.1

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  277. Deep-Learning-Based Segmentation for the Head Sectioned Images of the Visible Korean Project

    Mohammad Eshghi, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Min Suk Chung, Kensaku Mori

    MI2016-119   Vol. 116 ( 393 ) page: 191-194   2017.1

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  278. Influence of Voxel-Connection Structure in Organ Segmentation Based on Conditional Random Field

    Ying Yang, Masahiro Oda, Kazunari Misawa, Daniel Rueckert, Kensaku Mori

    MI2016-112   Vol. 116 ( 393 ) page: 157-162   2017.1

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  279. Structured Random Forestを用いた3次元腹部CT像からのリンパ節自動検出

    寳珠山 裕, Holger Roth, 小田 昌宏, 中村 嘉彦, 三澤 一成, 藤原 道隆, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 116 ( 393 ) page: 23-28   2017.1

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  280. MISTライブラリのためのGPUプログラミング

    小田 紘久, 小田 昌宏, 北坂 孝幸, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 116 ( 393 ) page: 133-136   2017.1

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  281. Robust colonoscope tracking method for colon deformations utilizing coarse-to-fine correspondence findings Reviewed International coauthorship

    Masahiro Oda, Hiroaki Kondo, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara ,Yoshiki Hirooka, Hidemi Goto, Nassir Navab, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 12 ( 1 ) page: 39-50   2017.1

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    DOI: 10.1007/s11548-016-1456-6

  282. Extracellular matrix directions estimation of the heart on micro-focus X-ray CT volumes Reviewed

    Oda Hirohisa, Oda Masahiro, Kitasaka Takayuki, Akita Toshiaki, Mori Kensaku

    MEDICAL IMAGING 2017: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING   Vol. 10137   2017

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    DOI: 10.1117/12.2254949

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  283. Evaluation of a cardiac model using different 3D printers and materials Reviewed

    Murata Masato, Hirayama Koudai, Takenouchi Sinsaku, Oda Masahiro, Mori Kensaku, Niki Kiyomi

    Transactions of Japanese Society for Medical and Biological Engineering   Vol. 55 ( 4 ) page: 273-273   2017

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    <p>[Purpose] Models of the diseased heart produced by 3D printers are expected to provide useful information for surgical procedures. However, the precision of commercially available machines is uncertain. Therefore, we assessed the 3D models by two different methods. [Method] Using DICOM data derived from x-ray CT images of a heart, 3D models were produced by a fused deposition modeling method (FDM) and an ink-jet method. Polylactic resin (PLA) and silicone rubber (AR-G1L) were used as materials for the FDM and ink-jet methods, respectively. [Result] The model created using the FDM was produced at a reduced size due to limitations of the machine, which caused the coronary artery to collapse. It was also difficult to cut. The model created using the ink-jet method was produced at full scale and quite flexible. [Conclusion] The heart model created using the ink-jet method with silicone rubber provides excellent information for surgical treatment.</p>

    DOI: 10.11239/jsmbe.55Annual.273

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  284. Automated endoscopic image analysis based on machine learning

    Mori Kensaku, Oda Masahiro, Misawa Masashi, Mori Yuichi, Kudo Shinei

    Transactions of Japanese Society for Medical and Biological Engineering   Vol. 55 ( 4 ) page: 344-344   2017

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    <p>This presentation introduces automated endoscopic image diagnosis method based on machine learning. Especially we discuss effectiveness of machine learning in automated diagnosis of endoscopic images by showing automated pathological type diagnosis of colonic polyps from endocytoscopy images as examples. Machine learning research staring from perceptron or statistical pattern recognition has started in many years ago. Progress of high performance computing has enabled us to train neural network having very complex network architecture. Machine learning techniques are considered to help physicians to diagnose endoscopic images, where very higher skills are required for diagnosis. This presentation will show several automated diagnosis methods for endoscopic images. The first method classifies pathological types of colonic polyps by using hand-crafted feature values. SVM is utilized for classification. The second example is the method using CNN for automated classification. We will show these method from the technological viewpoint. Also we will discuss about training data generation.</p>

    DOI: 10.11239/jsmbe.55Annual.344

  285. Motion Vector for Outlier Elimination in Feature Matching and Its Application in SLAM Based Laparoscopic Tracking Reviewed

    Wang Cheng, Oda Masahiro, Hayashi Yuichiro, Misawa Kazunari, Roth Holger, Mori Kensaku

    COMPUTER ASSISTED AND ROBOTIC ENDOSCOPY AND CLINICAL IMAGE-BASED PROCEDURES   Vol. 10550   page: 60-69   2017

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    DOI: 10.1007/978-3-319-67543-5_6

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  286. Airway extraction from 3D chest CT volumes based on iterative extension of VOI enhanced by cavity enhancement filter Reviewed

    Meng Qier, Kitasaka Takayuki, Oda Masahiro, Mori Kensaku

    SPIE MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS   Vol. 10134   2017

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    DOI: 10.1117/12.2254233

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  287. Micro-CT Guided 3D Reconstruction of Histological Images Reviewed

    Nagara Kai, Roth Holger R., Nakamura Shota, Oda Hirohisa, Moriya Takayasu, Oda Masahiro, Mori Kensaku

    PATCH-BASED TECHNIQUES IN MEDICAL IMAGING (PATCH-MI 2017)   Vol. 10530   page: 93-101   2017

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    DOI: 10.1007/978-3-319-67434-6_11

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  288. Hessian-Assisted Supervoxel: Structure-Oriented Voxel Clustering and Application to Mediastinal Lymph Node Detection from CT Volumes Reviewed International coauthorship

    Oda Hirosha, Bhatia Kanwal K., Oda Masahiro, Kitasaka Takayuki, Iwano Shingo, Homma Hirotoshi, Takabatake Hirotsugu, Mori Masaki, Natori Hiroshi, Schnabel Julia A., Mori Kensaku

    MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS   Vol. 10134   2017

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    DOI: 10.1117/12.2254782

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  289. Extraction of membrane structure in eyeball from MR volumes Reviewed

    Oda Masahiro, Kin Taichi, Mori Kensaku

    SPIE MEDICAL IMAGING 2017: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING   Vol. 10137   2017

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    DOI: 10.1117/12.2254095

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  290. Tracking and segmentation of the airways in chest CT using a fully convolutional network Reviewed

    Qier Meng, Holger R. Roth, Takayuki Kitasaka, Masahiro Oda, Junji Ueno, Kensaku Mori

    MICCAI 2017   Vol. 10434 LNCS   page: 198 - 207   2017

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    DOI: 10.1007/978-3-319-66185-8_23

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  291. TBS: Tensor-based supervoxels for unfolding the heart Reviewed International coauthorship

    Hirohisa Oda, Holger R. Roth, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Julia A. Schnabel, Kensaku Mori

    MICCAI 2017   Vol. 10433 LNCS   page: 681 - 689   2017

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    DOI: 10.1007/978-3-319-66182-7_78

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  292. Comparison of the Deep-Learning-Based Automated Segmentation Methods for the Head Sectioned Images of the Virtual Korean Human Project Reviewed

    Eshghi Mohammad, Roth Holger R., Oda Masahiro, Chung Min Suk, Mori Kensaku

    PROCEEDINGS OF THE FIFTEENTH IAPR INTERNATIONAL CONFERENCE ON MACHINE VISION APPLICATIONS - MVA2017     page: 290 - 293   2017

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  293. Automatic Segmentation of Head Anatomical Structures from Sparsely-annotated Images Reviewed

    Sugino Takaaki, Roth Holger R., Eshghi Mohammad, Oda Masahiro, Chung Min Suk, Mori Kensaku

    2017 IEEE INTERNATIONAL CONFERENCE ON CYBORG AND BIONIC SYSTEMS (CBS)     page: 145 - 149   2017

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  294. 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation Reviewed International coauthorship

    Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken’ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori

    MICCAI 2017, 3rd Workshop on Deep Learning in Medical Image Analysis   Vol. 10553   page: 222 - 230   2017

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    DOI: 10.1007/978-3-319-67558-9_26

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  295. Influence of using 3D images and 3D-printed objects on the formation of spatial mental models of experts and novices

    MAEHIGASHI Akihiro, MIWA Kazuhisa, ODA Masahiro, NAKAMURA Yoshihiko, MORI Kensaku, IGAMI Tsuyoshi

    JSAI Technical Report, SIG-ALST   Vol. 79 ( 0 )   2017

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    DOI: 10.11517/jsaialst.79.0_08

  296. Influence of using 3D images and 3D-printed objects on spatial reasoning of experts and novices

    Maehigashi A., Miwa K., Oda M., Nakamura Y., Mori K., Igami T.

    CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition     page: 2669 - 2674   2017

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    Language:Japanese   Publisher:CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition  

    This study focuses on the infuence of a three-dimensional (3D) graphic image and a 3D-printed object on the spatial reasoning of experts and novices in the medical field. The spatial reasoning task of this study required doctors specializing in digestive surgery to infer cross sections of a liver with a 3D image and a 3D-printed object in a situation where liver resection surgery was simulated. The task performance was compared with that of university students who conducted the same task in Maehigashi et al. (2016). The results of the analysis indicated that the doctors showed the same task performance when using the 3D image and the 3D-printed object. However, the university students learned faster and inferred the inside of a liver structure more accurately with the 3D-printed object than with the 3D image, and they performed equally to the professional doctors. Our results are then discussed in relation to previous studies.

    Scopus

  297. Impact of an automated system for endocytoscopic diagnosis of small colorectal lesions: an international web-based study Reviewed

    Yuichi Mori, Shin-ei Kudo ,Philip Wai Yan Chiu, Rajvinder Singh, Masashi Misawa, Kunihiro Wakamura, Toyoki Kudo, Takemasa Hayashi, Atsushi Katagiri, Hideyuki Miyachi, Fumio Ishida, Yasuharu Maeda, Haruhiro Inoue, Yukitaka Nimura, Masahiro Oda, Kensaku Mori

    Endoscopy   Vol. 48 ( 12 ) page: 1110 - 1118   2016.8

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1055/s-0042-113609

  298. Impact of an automated system for endocytoscopic diagnosis of small colorectal lesions: an international web-based study Reviewed

    Yuichi Mori, Shin-ei Kudo, Philip Wai Yan Chiu, Rajvinder Singh, Masashi Misawa, Kunihiro Wakamura, Toyoki Kudo, Takemasa Hayashi, Atsushi Katagiri, Hideyuki Miyachi, Fumio Ishida, Yasuharu Maeda, Haruhiro Inoue, Yukitaka Nimura, Masahiro Oda, Kensaku Mori

    Endoscopy   Vol. 48 ( 12 ) page: 1110 - 1118   2016.8

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1055/s-0042-113609

  299. Clinical application of a surgical navigation system based on virtual laparoscopy in laparoscopic gastrectomy for gastric cancer Reviewed International coauthorship

    Yuichiro Hayashi, Kazunari Misawa, Masahiro Oda, David J. Hawkes, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 11 ( 5 ) page: 827 - 836   2016.5

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/s11548-015-1293-z

  300. Clinical application of a surgical navigation system based on virtual laparoscopy in laparoscopic gastrectomy for gastric cancer Reviewed International coauthorship

    Yuichiro Hayashi, Kazunari Misawa, Masahiro Oda, David J. Hawkes, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 11 ( 5 ) page: 827 - 836   2016.5

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/s11548-015-1293-z

  301. Pneumoperitoneum simulation based on mass-spring-damper models for laparoscopic surgical planning Reviewed

    Yukitaka Nimura, Jia Di Qu, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Makoto Hashizume, Kazunari Misawa, and Kensaku Mori

    Journal of Medical Imaging   Vol. 2 ( 4 )   2015.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/1.JMI.2.4.044004

  302. Pneumoperitoneum simulation based on mass-spring-damper models for laparoscopic surgical planning Reviewed

    Yukitaka Nimura, Jia Di Qu, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Makoto Hashizume, Kazunari Misawa, and Kensaku Mori

    Journal of Medical Imaging   Vol. 2 ( 4 )   2015.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/1.JMI.2.4.044004

  303. Automated anatomical labeling of abdominal arteries and hepatic portal system extracted from abdominal CT volumes Reviewed

    Tetsuro Matsuzaki, Masahiro Oda, Takayuki Kitasaka, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    Medical Image Analysis   Vol. 20 ( 1 ) page: 152 - 161   2015.2

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1016/j.media.2014.11.002

  304. Automated anatomical labeling of abdominal arteries and hepatic portal system extracted from abdominal CT volumes Reviewed

    Tetsuro Matsuzaki, Masahiro Oda, Takayuki Kitasaka, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    Medical Image Analysis   Vol. 20 ( 1 ) page: 152 - 161   2015.2

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1016/j.media.2014.11.002

  305. Automated Ulcer Detection Method From CT Images for Computer Aided Diagnosis of Crohn's Disease Reviewed

    Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Osamu Watanabe, Takafumi Ando, Hidemi Goto, and Kensaku Mori

    IEICE Transactions on Information and Systems   Vol. E96-D ( 4 ) page: 808 - 818   2013.4

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1587/transinf.E96.D.808

  306. Digital Bowel Cleansing Free Colonic Polyp Detection Method for Fecal Tagging CT Colonography Reviewed

    Masahiro ODA, Takayuki KITASAKA, Kensaku MORI, Yasuhito SUENAGA, Tetsuji TAKAYAMA, Hirotsugu TAKABATAKE, Masaki MORI, Hiroshi NATORI, and Shigeru NAWANO

    Academic Radiology   Vol. 16 ( 4 ) page: 486 - 494   2009.4

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    Rationale and Objectives:
    Fecal tagging CT colonography (ftCTC) reduces the discomfort and the inconvenience of patients associated with bowel cleansing procedures prior to CT scanning. In conventional colonic polyp detection techniques for ftCTC, a digital bowel cleansing (DBC) technique is applied to detect polyps in tagged fecal materials (TFM). However, DBC removes the surface of soft tissues and hampers polyp detection. We developed a colonic polyp detection method for CT colonographic examination that enables the detection of polyps surrounded by air and polyps surrounded by TFM without DBC.

    Materials and Methods:
    CT values inside the polyps surrounded by air and polyps surrounded by TFM tend to gradually increase (blob structure) and decrease (inverse-blob structure) from outward to inward, respectively. We developed blob and inverse-blob structure enhancement filters based on the eigenvalues of a Hessian matrix to detect polyps using their intensity characteristic. False positive elimination is performed using three feature values: volume, maximum value of filter outputs, and standard deviation of CT values inside the polyp candidates.

    Results:
    The proposed method is applied to 104 cases of ftCTC images that include 57 polyps larger than 6 mm in diameter. The sensitivity of the method was 91.2% (52/57) with 11.4 false positives per case.

    Conclusion:
    The proposed method detects polyps with high sensitivity and 11.4 false positives per case without adverse effects on the DBC.

    DOI: 10.1016/j.acra.2008.10.011

  307. Digital bowel cleansing free colonic polyp detection method from fecal tagging CT images Reviewed

    Masahiro ODA, Takayuki KITASAKA, Kensaku MORI, Yasuhito SUENAGA, Tetsuji TAKAYAMA, Hirotsugu TAKABATAKE, Masaki MORI, Hiroshi NATORI, and Shigeru NAWANO

      Vol. J91-D ( 7 ) page: 1904 - 1913   2008.7

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    This paper proposes a method for the detection of colonic polyps from fecal tagging CT images without digital bowel cleansing (DBC). Previous polyp detection methods needed DBC to detect polyps which are surrounded by tagged fecal materials (TFM). However, DBC may changes shapes of polyps
    while removing TFM. Our method can detect polyps which are surrounded by air or TFM without any DBC processes. We employ blob and inverse-blob structure enhancement filters based on the eigenvalues of the Hessian matrix. As the results of experiments using 104 cases of abdominal CT images, sensitivity for polyps >= 6mm was 91.2% with 11.4 FPs/case.

  308. A Study on Method of Distortion Reduction of Virtual Unfolded Views of the Colon Reviewed

    Masahiro ODA, Yuichiro HAYASHI, Takayuki KITASAKA, Kensaku MORI, and Yasuhito SUENAGA

    Medical Imaging Technology   Vol. 24 ( 5 ) page: 419 - 428   2006.11

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    This paper proposes a method for reducing distortions of virtual unfolded (VU) views of the colon. VU views enable physicians to observe a large area of the colonic wall efficiently. A VU view is generated by flattening the colon to a plane on computer. In a previous method, VU views are generated by casting rays of volume rendering perpendicular to the centerline of the colon. However, rays intersected at curved areas of the colon and it caused spurious holes in the VU views. Our previous system generated VU views of a constant height regardless of the perimeter of the colon. Therefore, thin areas of the colon were stretched in the VU views, which caused distortions. In this paper, we propose two methods to improve the quality of VU views. We reduce ray intersections by employing a spring model. This method allocates springs between planes perpendicular to the centerline. Then plane directions are modified by spring forces, which lead to reduce the intersections of the planes. We also reduce distortions by changing the height of VU views according to the perimeter of the colon. We applied the method to eighteen cases of abdominal CT images. Experimental results showed that the method could generate VU views satisfactorily.

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Books 12

  1. 医療AIとディープラーニングシリーズ 内視鏡画像AI

    小田昌宏, 伊東隼人( Role: Contributor ,  Chapter19: AIによる内視鏡画像分類)

    株式会社オーム社  2022.11  ( ISBN:978-4-274-22564-2

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    Total pages:250   Responsible for pages:179-198   Language:Japanese Book type:Scholarly book

  2. 内視鏡画像AI

    森, 健策, 工藤, 進英, 森, 悠一, 三澤, 将史( Role: Contributor ,  Chapter19: AIによる内視鏡画像分類)

    オーム社  2022.11  ( ISBN:9784274225642

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    Total pages:xi, 236p   Language:Japanese

    CiNii Books

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  3. Precision Medicine 2022年11月号

    小田昌宏( Role: Contributor ,  仮説駆動型の医学からデータ駆動型の医学へ 5. 説明可能AIと不確実性解析による信頼されるAIの実現)

    北隆館  2022.10 

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  4. 月刊インナービジョン2022年7月号

    小田 昌宏( Role: Contributor ,  特集 II 医療AIを加速させる研究開発の動向 3. 医療AI開発におけるVision Transformerの可能性)

    INNERVISION  2022.6 

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  5. AI・ナノ・量子による超高感度・迅速バイオセンシング : 超早期パンデミック検査・超早期診断・POCTから健康長寿社会へ

    馬場, 嘉信, 柳田, 剛, 加地, 範匡( Role: Contributor ,  COVID-19肺炎CT画像のAI解析)

    シーエムシー出版  2021.8  ( ISBN:9784781316093

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    Total pages:vii, 244p   Language:Japanese

    CiNii Books

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  6. AI・ナノ・量子による超高感度・迅速バイオセンシング-超早期パンデミック検査・超早期診断・POCTから健康長寿社会へ-

    小田 昌宏( Role: Contributor ,  COVID-19肺炎CT画像のAI解析)

    シーエムシー出版  2021.8  ( ISBN:978-4-7813-1609-3

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    Total pages:244   Responsible for pages:93-100   Language:Japanese Book type:Scholarly book

  7. 医療AIとディープラーニングシリーズ 放射線治療AIと外科治療AI

    小田昌宏( Role: Contributor ,  AI外科治療編 Chapter3: 大腸の治療と診断におけるAI)

    株式会社オーム社  2020.4  ( ISBN:978-4-274-22547-5

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    Total pages:232   Responsible for pages:137-147   Language:Japanese Book type:Scholarly book

  8. 放射線治療AIと外科治療AI

    有村, 秀孝, 諸岡, 健一( Role: Contributor ,  AI外科治療編 Chapter3: 大腸の治療と診断におけるAI)

    オーム社  2020.4  ( ISBN:9784274225475

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    Total pages:xi, 217p   Language:Japanese

    CiNii Books

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  9. 臨床画像 35巻10号

    小田 昌宏( Role: Contributor ,  特集 今知りたい、AIの歴史とこれから,ディープラーニング実践の環境構築)

    メジカルビュー社  2019.10 

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  10. 医療AIとディープラーニングシリーズ 医用画像のためのディープラーニング-実践編-

    小田 昌宏( Role: Contributor ,  Chapter6: 動画像のシーン分割と分類, Chapter7: 画像のノイズ除去, Chapter8: 画像の超解像)

    株式会社オーム社  2019.7  ( ISBN:978-4-274-22363-1

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    Total pages:212   Responsible for pages:104-143   Language:Japanese Book type:Scholarly book

    Other Link: https://www.amazon.co.jp/dp/4274223639

  11. Applied Technologies and Systems

    Mori K., Niki N., Kawata Y., Fujita H., Oda M., Kim H., Arimura H., Shimizu A., Noriki S., Inai K., Kimura H.

    Computational Anatomy Based on Whole Body Imaging: Basic Principles of Computer-Assisted Diagnosis and Therapy  2017.6  ( ISBN:9784431559740

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    This chapter shows applied technologies using computational anatomy (CA) models. CA systems based on clinical images assist physicians by providing useful information related to diagnostic and therapeutic procedures. Such systems include computer-aided diagnosis and computer-assisted surgery systems. A thorough understanding of anatomy is essential when designing these systems. It is important to understand how anatomical information extracted by a computer is used. In this chapter, we introduce applications of CA in three categories: (a) computer-aided diagnosis, (b) computer-assisted therapy and intervention, and (c) computer-assisted autopsy imaging. The technical details of these applications are discussed.

    DOI: 10.1007/978-4-431-55976-4_4

    Scopus

  12. 実践 医用画像解析ハンドブック

    小田昌宏( Role: Contributor ,  3.2.1 特徴抽出, 6.2.1.1.[2] CT画像における大腸のセグメンテーション)

    株式会社オーム社  2012.11  ( ISBN:978-4-274-21282-6

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    Total pages:898   Language:Japanese Book type:Scholarly book

    医用画像の解析とその臨床への応用についての様々な技術の解説を掲載したもの

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MISC 32

  1. 生成AIの仕組みと医療応用 Invited

    小田昌宏

    月刊インナービジョン2023年7月号   Vol. 38 ( 7 ) page: 36 - 39   2023.6

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Rapid communication, short report, research note, etc. (scientific journal)  

  2. Participating Report of MICCAI 2022 Invited

    Masahiro Oda

    Medical Imaging and Information Sciences   Vol. 39 ( 4 ) page: 78 - 81   2022.12

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    Authorship:Lead author, Last author, Corresponding author   Language:Japanese   Publishing type:Meeting report  

    DOI: https://doi.org/10.11318/mii.39.78

  3. Explainable AI and uncertainty analysis for trustworthy AI Invited

    Masahiro Oda

    Precision Medicine     page: 26 - 29   2022.10

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    Authorship:Lead author, Last author, Corresponding author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

  4. Research Trends of Surgical Assistance AI: Introduction Invited

    Medical Imaging Technology   Vol. 40 ( 4 ) page: 149 - 150   2022.9

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    Authorship:Lead author, Last author, Corresponding author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

    DOI: https://doi.org/10.11409/mit.40.149

  5. 医療AI開発におけるVision Transformerの可能性 Invited

    小田 昌宏

    月刊インナービジョン2022年7月号   Vol. 37 ( 7 ) page: 28 - 31   2022.6

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    Authorship:Lead author, Last author, Corresponding author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

  6. nnU-Netによる肺マイクロCT像からの小葉間隔壁抽出

    深井 大輔, 小田 紘久, 椎名 健, 林 雄一郎, 鄭 通, 中村 彰太, 小田 昌宏, 森 健策

    日本コンピュータ外科学会誌   Vol. 24 ( 2 ) page: 133 - 134   2022.6

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    Language:Japanese   Publisher:(一社)日本コンピュータ外科学会  

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  7. Towards Explainable Artificial Intelligence: Introduction Invited

    Medical Imaging Technology   Vol. 39 ( 3 ) page: 97 - 98   2021.5

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    Authorship:Last author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

    DOI: https://doi.org/10.11409/mit.39.97

  8. 深層学習による画像認識入門 GPU環境構築と画像の領域分割 Invited

    原 武史, 小田 昌宏

    Medical Imaging Technology   Vol. 39 ( 3 ) page: 124 - 130   2021.5

  9. CT画像XAI技術で「新型コロナウィルス肺炎」を85%精度で識別 Invited

    小田 昌宏, 森 健策

    C-press   Vol. 120   page: 5 - 6   2021.2

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    Authorship:Lead author   Language:Japanese   Publishing type:Internal/External technical report, pre-print, etc.  

  10. Development of Diagnosis Assistant AI for COVID-19 Patients Invited

    Medical Imaging Technology   Vol. 39 ( 1 ) page: 13 - 19   2021.1

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

    DOI: https://doi.org/10.11409/mit.39.13

  11. Micro CT Image-Assisted Cross Modality Super-Resolution of Clinical CT Images Utilizing Synthesized Training Dataset

    Tong Zheng, Hirohisa Oda, Masahiro Oda, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

    CoRR   Vol. abs/2010.10207   2020.10

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    This paper proposes a novel, unsupervised super-resolution (SR) approach for
    performing the SR of a clinical CT into the resolution level of a micro CT
    ($\mu$CT). The precise non-invasive diagnosis of lung cancer typically utilizes
    clinical CT data. Due to the resolution limitations of clinical CT (about $0.5
    \times 0.5 \times 0.5$ mm$^3$), it is difficult to obtain enough pathological
    information such as the invasion area at alveoli level. On the other hand,
    $\mu$CT scanning allows the acquisition of volumes of lung specimens with much
    higher resolution ($50 \times 50 \times 50 \mu {\rm m}^3$ or higher). Thus,
    super-resolution of clinical CT volume may be helpful for diagnosis of lung
    cancer. Typical SR methods require aligned pairs of low-resolution (LR) and
    high-resolution (HR) images for training. Unfortunately, obtaining paired
    clinical CT and $\mu$CT volumes of human lung tissues is infeasible.
    Unsupervised SR methods are required that do not need paired LR and HR images.
    In this paper, we create corresponding clinical CT-$\mu$CT pairs by simulating
    clinical CT images from $\mu$CT images by modified CycleGAN. After this, we use
    simulated clinical CT-$\mu$CT image pairs to train an SR network based on
    SRGAN. Finally, we use the trained SR network to perform SR of the clinical CT
    images. We compare our proposed method with another unsupervised SR method for
    clinical CT images named SR-CycleGAN. Experimental results demonstrate that the
    proposed method can successfully perform SR of clinical CT images of lung
    cancer patients with $\mu$CT level resolution, and quantitatively and
    qualitatively outperformed conventional method (SR-CycleGAN), improving the
    SSIM (structure similarity) form 0.40 to 0.51.

    arXiv

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    Other Link: http://arxiv.org/pdf/2010.10207v1

  12. 畳み込みニューラルネットワークによるクロスフェーズCT画像位置合わせ

    胡 涛, 小田 昌宏, 林 雄一郎, 魯 仲陽, 隈丸 加奈子, 青木 茂樹, 森 健策

    日本医用画像工学会大会予稿集   Vol. 39回   page: 37 - 37   2020.9

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    Language:English   Publisher:(一社)日本医用画像工学会  

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  13. カラー写真を用いた角膜浸潤のAI自動分類の試み

    上野 勇太, 小田 昌宏, 山口 剛史, 福岡 秀記, 森 健策, 大鹿 哲郎

    日本眼科学会雑誌   Vol. 124 ( 臨増 ) page: 251 - 251   2020.3

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    Language:Japanese   Publisher:(公財)日本眼科学会  

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  14. 深層学習を用いた医用画像処理研究の最前線 Invited

    小田 昌宏

    画像通信   Vol. 42 ( 2 ) page: 2 - 7   2019.10

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    Authorship:Lead author   Language:Japanese   Publishing type:Internal/External technical report, pre-print, etc.  

  15. ディープラーニング実践の環境構築 Invited

    小田 昌宏

    臨床画像   Vol. 35 ( 10 ) page: 1120 - 1128   2019.9

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    Authorship:Lead author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

    DOI: doi.org/10.18885/J01843.2020039296

  16. 特集/医用画像処理におけるGenerative Adversarial Networks の利用 Invited

    小田 昌宏

    Medical Imaging Technology   Vol. 37 ( 3 ) page: 123 - 124   2019.5

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    Authorship:Lead author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

  17. 20mm以上の大腸病変に対するコンピューター自動診断システムの浸潤癌診断性能に関する検討

    加賀 浩之, 工藤 進英, 武田 健一, 森 悠一, 片岡 伸一, 前田 康晴, 小川 悠史, 一政 克朗, 三澤 将史, 工藤 豊樹, 若村 邦彦, 馬場 俊之, 日高 英二, 石田 文生, 井上 晴洋, 小田 昌宏, 森 健策, 山野 三紀

    日本大腸肛門病学会雑誌   Vol. 72 ( 5 ) page: 262 - 262   2019.5

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    Language:Japanese   Publisher:(一社)日本大腸肛門病学会  

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  18. 「大腸画像強調内視鏡の現状と未来」 人工知能(AI)に基づく大腸内視鏡検査によるリアルタイム病変検出支援システム

    趙 智成, 工藤 進英, 三澤 将史, 前田 康晴, 武田 健一, 一政 克朗, 中村 大樹, 矢川 裕介, 豊嶋 直也, 森 悠一, 小形 典之, 工藤 豊樹, 久行 友和, 林 武雅, 若村 邦彦, 馬場 俊之, 石田 文生, 伊東 隼人, 小田 昌宏, 森 健策

    日本大腸検査学会雑誌   Vol. 35 ( 2 ) page: 112 - 112   2019.4

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    Language:Japanese   Publisher:(社)日本大腸検査学会  

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  19. 名古屋大学の取り組み:放射線画像診断支援と内視鏡画像解析 Invited

    小田昌宏, 申 忱, 小田紘久, 森 健策

    Medical Imaging Technology   Vol. 37 ( 2 ) page: 84 - 88   2019.3

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    Authorship:Lead author   Language:Japanese  

  20. Segmentation of Stomach Wall on Micro-CT Volumes using Multi-scale Representation Learning

    御手洗翠, 小田紘久, 杉野貴明, 守谷享泰, 伊東隼人, 小田昌宏, 小宮山琢真, 古川和宏, 宮原良二, 藤城光弘, 森雅樹, 高畠博嗣, 名取博, 森健策, 森健策, 森健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 (Web) )   2019

  21. Forceps region segmentation on laparoscopic movies using data augmentation based on 3D models of forceps

    小澤卓也, 小田紘久, 伊東隼人, 北坂孝幸, 林雄一郎, 小田昌宏, 三澤一成, 竹下修由, 伊藤雅昭, 森健策, 森健策, 森健策

    日本コンピュータ外科学会誌   Vol. 21 ( 4 (Web) )   2019

  22. 【マイクロ解剖学のための微細解剖構造イメージング】デスクトップ型マイクロCTによる微細解剖構造イメージング

    森 健策, 中村 彰太, 秋田 利明, 小田 紘久, ホルガー・ロス, 小田 昌宏

    MEDICAL IMAGING TECHNOLOGY   Vol. 36 ( 3 ) page: 127 - 131   2018.5

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    Language:Japanese   Publisher:日本医用画像工学会  

    本稿では、デスクトップ型マイクロCTを用いた微細構造イメージングについて述べる。臨床の場で利用されるX線CT装置は、その解像度がおおよそ1ボクセルあたり0.5mmから1mm程度である。このようなイメージング装置を用いて得ることができる画像は、このボクセル解像度に準じた解剖構造を得ることができる。一方、マイクロCT装置を用いれば、1μmから50μm程度の解像度で撮影できる。本稿では、マイクロCTによって撮影された肺標本ならびに心臓標本を示し、その可能性について述べる。(著者抄録)

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  23. 人工知能に基づく大腸内視鏡のポリープ自動検出ソフトウェア

    三澤 将史, 工藤 進英, 森 悠一, 片岡 伸一, 中村 大樹, 武田 健一, 矢川 裕介, 一政 克朗, 石垣 智之, 豊嶋 直也, 小形 典之, 工藤 豊樹, 久行 友和, 林 武雅, 若村 邦彦, 馬場 俊之, 石田 文生, 伊東 隼人, 小田 昌宏, 森 健策

    Gastroenterological Endoscopy   Vol. 60 ( Suppl.1 ) page: 704 - 704   2018.4

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    Language:Japanese   Publisher:(一社)日本消化器内視鏡学会  

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  24. Feature-selection method based on Grassmann distance for the classification of neoplastic polyps on endocytoscopic images (医用画像)

    伊東 隼人, 森 悠一, 三澤 将史, 小田 昌宏, 工藤 進英, 森 健策

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   Vol. 117 ( 518 ) page: 51 - 56   2018.3

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    Language:English   Publisher:電子情報通信学会  

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  25. 特集/医用画像処理におけるディープラーニング利用入門 Invited

    小田 昌宏

    Medical Imaging Technology   Vol. 36 ( 2 ) page: 45 - 46   2018.3

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    Authorship:Lead author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

  26. ディープラーニング活用の重要ポイント Invited

    小田 昌宏

    Medical Imaging Technology   Vol. 36 ( 2 ) page: 72 - 75   2018.3

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    Authorship:Lead author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

  27. Kerasによるディープラーニング Invited

    小田 昌宏

    Medical Imaging Technology   Vol. 36 ( 2 ) page: 47 - 51   2018.3

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    Authorship:Lead author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

  28. Classification of neoplasia and non-neoplasia for colon endocytoscopic images by convolutional neural network

    伊東 隼人, 森 悠一, 三澤 将史, 小田 昌宏, 工藤 進英, 森 健策

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   Vol. 117 ( 220 ) page: 17 - 21   2017.9

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  29. 大腸・小腸疾患に対する診断の進歩 人工知能による、リアルタイム大腸内視鏡診断への挑戦

    森 悠一, 工藤 進英, 三澤 将史, 武田 健一, 一政 克朗, 前田 康晴, 石垣 智之, 若村 邦彦, 林 武雅, 小田 昌宏, 伊東 隼人, 森 健策

    日本大腸肛門病学会雑誌   Vol. 70 ( 抄録号 ) page: A71 - A71   2017.9

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  30. 人工知能によるSessile serrated adenoma/polyp診断は可能か?

    森 悠一, 工藤 進英, 小川 悠史, 三澤 将史, 武田 健一, 若村 邦彦, 工藤 豊樹, 林 武雅, 豊嶋 直也, 中村 大樹, 一政 克朗, 前田 康晴, 片岡 敦, 馬場 俊之, 石田 文生, 山野 三紀, 小田 昌宏, 森 健策

    Gastroenterological Endoscopy   Vol. 59 ( Suppl.1 ) page: 981 - 981   2017.4

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  31. Automated Anatomical Labeling of Abdominal Arteries Using Conditional Random Fields With Contrast Sensitive Potentials

      Vol. 116 ( 528 ) page: 137 - 142   2017.3

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    CiNii Books

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  32. Robust colonoscope tracking method for colon deformations utilizing coarse-to-fine correspondence findings Reviewed

    Masahiro Oda, Hiroaki Kondo, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Nassir Navab, Kensaku Mori

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 12 ( 1 ) page: 39 - 50   2017.1

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    Language:English   Publishing type:Rapid communication, short report, research note, etc. (scientific journal)   Publisher:SPRINGER HEIDELBERG  

    Polyps found during CT colonography can be removed by colonoscopic polypectomy. A colonoscope navigation system that navigates a physician to polyp positions while performing the colonoscopic polypectomy is required. Colonoscope tracking methods are essential for implementing colonoscope navigation systems. Previous colonoscope tracking methods have failed when the colon deforms during colonoscope insertions. This paper proposes a colonoscope tracking method that is robust against colon deformations.
    The proposed method generates a colon centerline from a CT volume and a curved line representing the colonoscope shape (colonoscope line) by using electromagnetic sensors. We find correspondences between points on a deformed colon centerline and colonoscope line by a landmark-based coarse correspondence finding and a length-based fine correspondence finding processes. Even if the coarse correspondence finding process fails to find some correspondences, which occurs with colon deformations, the fine correspondence finding process is able to find correct correspondences by using previously recorded line lengths.
    Experimental results using a colon phantom showed that the proposed method finds the colonoscope tip position with tracking errors smaller than 50 mm in most trials. A physician who specializes in gastroenterology commented that tracking errors smaller than 50 mm are acceptable. This is because polyps are observable from the colonoscope camera when positions of the colonoscope tip and polyps are closer than 50 mm.
    We developed a colonoscope tracking method that is robust against deformations of the colon. Because the process was designed to consider colon deformations, the proposed method can track the colonoscope tip position even if the colon deforms.

    DOI: 10.1007/s11548-016-1456-6

    Web of Science

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Presentations 285

  1. 手術支援AI開発に資する医用画像処理 Invited

    小田 昌宏

    第124回日本外科学会定期学術集会  2024.4.20  一般社団法人 日本外科学会

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    Event date: 2024.4

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:Aichi Sky Expo   Country:Japan  

  2. 眼底画像からの性別推定AIモデルの使用法 Invited

    小田 昌宏

    JOIR第2回データ利活用セミナー  2024.3.21  一般社団法人 Japan Ocular Imaging Registry

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    Event date: 2024.3

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:オンライン   Country:Japan  

  3. Latest Research Trends 2023: Image Segmentation and General Overview of MICCAI Invited

    Masahiro Oda, Itaru Otomaru, Ryo Furukawa, Kensaku Mori

    2024.3.3 

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    Event date: 2024.3

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Country:Japan  

  4. Impact of Generative AI in Medical Image Processing Invited International conference

    Masahiro Oda

    The Twelfth International Workshop on Image Media Quality and its Applications (IMQA 2024)  2024.2.28 

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    Event date: 2024.2

    Language:English   Presentation type:Oral presentation (keynote)  

    Venue:Osaka University Nakanoshima Cente   Country:Japan  

  5. 上級演題⑥ どうする研究費獲得:継続的な研究費獲得のための考え方 Invited

    小田 昌宏

    第32回日本コンピュータ外科学会大会  2023.12.2  日本コンピュータ外科学

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    Event date: 2023.12

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:かごしま県民交流センター   Country:Japan  

  6. 生成AIがもたらす医用画像処理の変革 Invited

    小田 昌宏

    医用画像情報学会 令和5年度秋季(第197回)大会  2023.10.7  医用画像情報学会

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    Event date: 2023.10

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:札幌 アスティ45 ACU会場   Country:Japan  

  7. 医療支援における画像処理研究の動向と展望 Invited

    小田 昌宏

    第29回画像センシングシンポジウム  2023.6.15  画像センシング技術研究会

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    Event date: 2023.6

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:パシフィコ横浜   Country:Japan  

  8. 内視鏡画像AIにおける実世界を考慮したデータ生成の必要性 Invited

    小田 昌宏

    次世代内視鏡・医工連携シンポジウム  2023.3.20 

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    Event date: 2023.3

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

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  9. Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes International conference

    Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2613317

  10. Size-reweighted cascaded fully convolutional network for substantia nigra segmentation from T2 MRI International conference

    Tao Hu, Hayato Itoh, Masahiro Oda, Shinji Saiki, Nobutaka Hattori, Koji Kamagata, Shigeki Aoki, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2613298

  11. Substantia nigra analysis by tensor decomposition of T2-weighted images for Parkinson’s disease diagnosis International conference

    Hayato Itoh, Masahiro Oda, Shinji Saiki, Nobutaka Hattori, Koji Kamagata, Shigeki Aoki, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2612830

  12. Self-supervised depth estimation with uncertainty-weight joint loss function based on laparoscopic videos International conference

    Wenda Li, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2612829

  13. Spatial label smoothing via aleatoric uncertainty for bleeding region segmentation from laparoscopic videos International conference

    Jie Qiu, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Nobuyoshi Takeshita, Masaaki Ito, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2611672

  14. Effective hyperparameter optimization with proxy data for multi-organ segmentation International coauthorship International conference

    Chen Shen, Holger R. Roth, Vishwesh Nath, Yuichiro Hayashi, Masahiro Oda, Kazunari Misawa, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2611422

  15. Coarse-to-fine cascade framework for cross-modality super-resolution on clinical/micro CT dataset International conference

    Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Masahiro Oda, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2611311

  16. Bronchial orifice tracking-based branch level estimation for bronchoscopic navigation International conference

    Cheng Wang, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Hitotsugu Takabatake, Masaki Mori, Hirotoshi Honma, Hiroshi Natori, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2612827

  17. Taking full advantage of uncertainty estimation: an uncertainty-assisted two-stage pipeline for multi-organ segmentation International conference

    Zhou Zheng, Masahiro Oda, Kazunari Misawa, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2612535

  18. Multiclass prediction for improving intestine segmentation on non-fecal-tagged CT volume International conference

    Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Aitaro Takimoto, Akinari,Hinoki, Hiroo Uchida, Kojiro Suzuki, Masahiro Oda, Kensaku Mori

    SPIE Medical Imaging 2022 On Demand  2022.3.21 

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    Event date: 2022.3

    Language:English   Presentation type:Oral presentation (general)  

    DOI: 10.1117/12.2611441

  19. 深層学習に基づくマウスのクラニアルウィンドウ画像における血管セグメンテーションの考察

    呉 運恒, 小田 昌宏, 林 雄一郎, 武部 貴則, 森 健策

    電子情報通信学会医用画像研究会  2022.1.27 

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    Event date: 2022.1

    Language:Japanese   Presentation type:Oral presentation (general)  

  20. 胸部CT像からのCOVID-19に関連した所見文の自動生成の検討

    岡崎 真治, 林 雄一郎, 小田 昌宏, 橋本 正弘, 陣崎 雅弘, 明石 敏昭, 青木 茂樹, 森 健策

    電子情報通信学会医用画像研究会  2022.1.26 

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    Event date: 2022.1

    Language:Japanese   Presentation type:Oral presentation (general)  

  21. MICCAI 2021参加報告 Invited

    伊東 隼人, 小田 昌宏, 申 忱, 大竹 義人, 花岡 昇平, 諸岡 健一, 本谷 秀堅, 古川 亮, 増谷 佳孝, 森 健策

    電子情報通信学会医用画像研究会  2022.1.26 

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    Event date: 2022.1

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

  22. 高精度な大腸ポリープ検出に向けた物体検出モデルの解析

    伊東 隼人, 三澤 将史, 森 悠一, 工藤 進英, 小田 昌宏, 森 健策

    電子情報通信学会医用画像研究会  2022.1.26 

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    Event date: 2022.1

    Language:Japanese   Presentation type:Oral presentation (general)  

  23. Mechanism Of AIs In COVID-19 CAD And Techniques To Improve AI Performance International conference

    Masahiro Oda, Yuichiro Hayashi, Zheng Tong, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori, Masahiro Hashimoto, Hiroshi Natori

    RSNA 2021  2021.11.28 

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    Event date: 2021.11 - 2021.12

    Language:English   Presentation type:Oral presentation (general)  

  24. Micro CT Assisted Cross-Modality Super-Resolution Towwrd Observing Micrometer-scale Anatomical Structure From Clinical CT tilizing AI International conference

    Tong Zheng, Hirohisa Oda, Yuichiro Hyashi, Masahiro Oda, Shota Nakamura, Hiroshi Natori, HIrotsugu Takabetake, Masaki Mori, Kensaku Mori

    RSNA 2021  2021.11.28 

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    Event date: 2021.11 - 2021.12

    Language:English   Presentation type:Oral presentation (general)  

  25. How Does AI Reconstruct 3D Intestinal Structures of Ileus and Intestinal Obstruction Cases From 3D CT? - Toward AI-based Emergency Diagnostic Assistance of Intestial Diseases International conference

    Hirohisa Oda, Yuichiro Hyashi, Masahiro Oda, Akinari Hinoki, HIroo Uchida, Kensaku Mori, Tkayuki Kitasaka, Aitaro Takimoto, Kojiro Suzuki

    RSNA 2021  2021.11.28 

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    Event date: 2021.11 - 2021.12

    Language:English   Presentation type:Oral presentation (general)  

  26. 自己教師あり学習による腹腔鏡動画像の手術器具セグメンテーション

    丘 傑,林 雄一郎,小澤 卓也,小田 昌宏, 北坂 孝幸,三澤 一成, 竹下 修由, 伊藤 雅昭, 森 健策

    第30回日本コンピュータ外科学会大会  2021.11.21 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

  27. 腹腔鏡下胃切除術支援に向けた腹腔鏡映像からの左胃静脈領域自動抽出に関する検討

    榎本 圭吾,林 雄一郎,北坂 孝幸,小田 昌宏, 伊藤 雅昭, 竹下 修由, 三澤 一成, 森 健策

    第30回日本コンピュータ外科学会大会  2021.11.23 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

  28. 複数の畳み込み範囲を持つグラフニューラルネットワークによる血管名自動命名手法の検討

    出口 智也,林 雄一郎,北坂 孝幸,小田 昌宏, 三澤 一成,森 健策

    第30回日本コンピュータ外科学会大会  2021.11.23 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

  29. 小田紘久,林 雄一郎,北坂 孝幸,滝本 愛太朗,檜 顕成,内田 広夫,鈴木 耕次郎,小田 昌宏, 森 健策

    CT像からの腸管領域抽出改善に関する基礎的検討

    第30回日本コンピュータ外科学会大会  2021.11.23 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

  30. CT像の非等方性を考慮した3D CNNによるCOVID‒19症例の自動分類手法

    小田 昌宏, 鄭 通, 林 雄一郎, 大竹 義人, 橋本 正弘, 明石 敏明, 青木 茂樹, 森 健策

    第30回日本コンピュータ外科学会大会  2021.11.22 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

  31. 大規模腹腔鏡動画像データベース構築に向けたアノテーションツール開発

    伊東 隼人,潘 冬平,小澤 卓也,小田 昌宏, 竹下 修由, 伊藤 雅昭, 森 健策

    第30回日本コンピュータ外科学会大会  2021.11.22 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

  32. 距離変換と管状構造フィルタによる肺マイクロCT画像からの細気管支・肺胞管抽出手法の検討

    椎名 健, 小田 紘久, 鄭 通, 中村 彰太, 林 雄一郎, 小田 昌宏, 森 健策

    第30回日本コンピュータ外科学会大会  2021.11.21 

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    Event date: 2021.11

    Language:Japanese   Presentation type:Oral presentation (general)  

  33. Graph Cuts Loss to Boost Model Accuracy and Generalizability for Medical Image Segmentation International conference

    Zhou Zheng, Masahiro Oda, Kensaku Mori

    IEEE/CVF International Conference on Computer Vision (ICCV) Workshops  2021.10.17 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  34. 胸部CT像からのCOVID-19症例の自動分類手法

    小田 昌宏, 鄭 通, 林 雄一郎, 大竹 義人, 橋本 正弘, 明石 敏昭, 森 健策

    第40回日本医用画像工学会大会  2021.10.13 

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    Event date: 2021.10

    Language:Japanese   Presentation type:Oral presentation (general)  

  35. Self-attention Class Balanced DenseNet_LSTM framework for Subarachnoid Hemorrhage CT image Classification on Extremely Imbalanced Brain CT Dataset

    Zhongyang LU,Masahiro ODA,Yuichiro HAYASHI,Tao HU,Hayato ITOH,Takeyuki WATADANI,Osamu ABE, Masahiro HASHIMOTO, Masahiro JINZAKI, Kensaku MORI

    2021.10.13 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  36. 腸閉塞・イレウスの病変箇所特定における診断支援システムの精度評価

    小田 紘久, 林 雄一郎, 北坂 孝幸, 玉田 雄大, 滝本 愛太朗, 檜 顕成, 内田 広夫, 鈴木 耕次郎, 小田 昌宏, 森 健策

    第40回日本医用画像工学会大会  2021.10.13 

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    Event date: 2021.10

    Language:Japanese   Presentation type:Oral presentation (general)  

  37. Improving Classification Accuracy of Hands' Bone Marrow Edema by Transfer Learning

    Dongping PAN, Masahiro ODA, Kou KATAYAMA, Takanobu Okubo, Kensaku MORI

    2021.10.13 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  38. Transformer ベースのモデルを用いた肺領域における所見文からの疾患名抽出

    岡崎 真治, 林 雄一郎, 小田 昌宏, 橋本 正弘, 陣崎 雅弘, 明石 敏昭, 青木 茂樹, 森 健策

    第40回日本医用画像工学会大会  2021.10.14 

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    Event date: 2021.10

    Language:Japanese   Presentation type:Oral presentation (general)  

  39. Synthesized Perforation Detection from Endoscopy Videos Using Model Training with Synthesized Images by GAN

    Kai Jiang, Hayato Itoh, Masahiro Oda, Taishi Okumura, Yuichi Mori, Masashi Misawa, Takemasa Hayashi, Shin-Ei Kudo, Kensaku Mori

    2021.10.14 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  40. Vascular Structure Segmentation in Stereomicroscope Image

    Yunheng WU, Masahiro ODA, Yuichiro HAYASHI, Takanori TAKEBE, Kensaku MORI

    2021.10.14 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  41. VR Organ Puzzle: A Virtual Reality Application for the Education of Human Anatomy

    Siqi LI, Yuichiro HAYASHI,Michitaka FUJIWARA, Masahiro ODA, Kensaku MORI

    2021.10.15 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  42. Non-contrast to Artery Contrast CT Translation Via Representation-Aligned Generative Model

    Tao HU, Masahiro ODA, Yuichiro HAYASHI, Zhongyang LU, Toshiaki AKASHI, Shigeki AOKI, Kensaku MORI

    2021.10.15 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  43. Clinical CT Super-resolution Utilizing Registered Clinical – Micro CT Database

    Tong ZHENG, Hirohisa ODA, Yuichiro HAYASHI, Shota NAKAMURA, Masaki MORI, Hirotsugu TAKABATAKE, Hiroshi NATORI, Masahiro ODA, Kensaku MORI

    2021.10.15 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  44. 距離マップを利用した肺マイクロ CT 像からの肺胞抽出

    椎名 健, 小田 紘久, 鄭 通, 中村 彰太, 林 雄一郎, 小田 昌宏, 森 健策

    第40回日本医用画像工学会大会  2021.10.15 

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    Language:Japanese   Presentation type:Oral presentation (general)  

  45. ピットパターン特徴量の解析に向けた超拡大内視鏡画像の再構成法に関する初期的検討

    伊東 隼人, 小田 昌宏, 森 悠一, 三澤 将史, 工藤 進英, 森 健策

    第40回日本医用画像工学会大会  2021.10.14 

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    Language:Japanese   Presentation type:Oral presentation (general)  

  46. 深層学習とディジタルファントムを用いた骨陰影低減技術の開発

    五島 風汰, 田中 利恵, 小田 昌宏, 森 健策, 高田 宗尚, 田村 昌也, 松本 勲

    第40回日本医用画像工学会大会  2021.10.14 

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    Event date: 2021.10

    Language:Japanese   Presentation type:Oral presentation (general)  

  47. 3D Kidney Tumor Semantic Segmentation using Cascaded Convolutional Networks

    Wuyang Zhao,Chen Shen,Masahiro Oda, Yuichiro Hayashi,Naoki Higashida,Msahiro Hashimoto,Masahiro Jinzaki, Kensaku Mori

    2021.10.14 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  48. Attention機構を導入したグラフニューラルネットワークによる腹部動脈血管名自動対応付け

    出口 智也, 林 雄一郎, 北坂 孝幸, 小田 昌宏, 三澤 一成, 森 健策

    第40回日本医用画像工学会大会  2021.10.14 

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    Event date: 2021.10

    Language:Japanese   Presentation type:Oral presentation (general)  

  49. 深度情報を利用したFCNによる腹腔鏡映像からの血管領域自動抽出の検討

    榎本 圭吾, 林 雄一郎, 北坂 孝幸, 小田 昌宏, 伊藤 雅昭, 竹下 修由, 三澤 一成, 森 健策

    第40回日本医用画像工学会大会  2021.10.14 

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    Event date: 2021.10

    Language:Japanese   Presentation type:Oral presentation (general)  

  50. Carotid Artery Vessel Wall Segmentation Challenge Report,'' Carotid Artery Vessel Wall Segmentation Challenge International conference

    Ruiyun Zhu, Masahiro Oda, Yuichiro Hayashi, Hideki Ota,Hitomi Anzai, Makoto Ohta, Takanobu Yagi, Masaaki Shojima, Soichiro Fujimura, Kensaku Mori

    SMRA 2021 and MICCAI 2021  2021.10.1 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

  51. Super-Resolution by Latent Space Exploration: Training with Poorly-Aligned Clinical and Micro CT Image Dataset International conference

    Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masahiro Oda, Kensaku Mori

    International Workshop on Simulation and Synthesis in Medical Imaging SASHIMI 2021  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  52. Multi-task Federated Learning for Heterogeneous Pancreas Segmentation International coauthorship International conference

    Chen Shen, Pochuan Wang, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Weichung Wang, Chiou-Shann Fuh, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Kensaku Mori

    CLIP2021  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  53. Self-supervised Cascaded Multi-task Learning on Laparoscopic Videos for Depth Estimation in Robotic-assisted Surgery International conference

    Wenda Li, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

    IROS2021 Workshop  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  54. Spatially-variant Biases Considered Self-supervised Depth Estimation Based on Laparoscopic Videos International conference

    Wenda Li, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

    Joint MICCAI workshop 2021, AE-CAI/CARE/OR2.0  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  55. Depth Estimation from Single-shot Monocular Endoscope Image Using Image Domain Adaptation And Edge-Aware Depth Estimation International conference

    Masahiro Oda, Hayato Itoh, Kiyohito Tanaka, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    Joint MICCAI workshop 2021, AE-CAI/CARE/OR2.0  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  56. Uncertainty Meets 3D-Spatial Feature in Colonoscopic Polyp-Size Determination International conference

    Hayato Itoh, Masahiro Oda, Kai Jiang, Yuichi Mori, Masashi Misawa, Shin-Ei Kudo, Kenichiro Imai, Sayo Itoh, Kinichi Hotta, Kensaku Mori

    Joint MICCAI workshop 2021, AE-CAI/CARE/OR2.0  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  57. Intestine segmentation with small computational cost for diagnosis assistance of ileus and intestinal obstruction International conference

    Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Masahiro Oda, Kensaku Mori

    CLIP2021  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  58. COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty International conference

    Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

    CLIP2021  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  59. Attention-guided pancreatic duct segmentation from abdominal CT volumes International coauthorship International conference

    Chen Shen, Holger Roth, Yuichiro Hayashi, Masahiro Oda, Takaaki Miyamoto, Gen Sato, Kensaku Mori

    CLIP2021  2021.9.27 

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    Event date: 2021.9

    Language:English   Presentation type:Oral presentation (general)  

  60. Micro-CT-assisted cross-modality super-resolution of clinical CT: utilization of synthesized training dataset International conference

    T. Zheng, H. Oda, S. Nakamura, M. Mori, H. Takabatake, H. Natori, M. Oda, K. Mori

    CARS 2021  2021.6.21 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  61. Spatial Information Considered Module based on Attention Mechanism for Self-Supervised Depth Estimation from Laparoscopic Image Pairs International conference

    W. Li, Y. Hayashi, M. Oda, T. Kitasaka, K. Misawa, K. Mori

    CARS 2021  2021.6.23 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  62. Real-time deformation simulation of hollow organs based on XPBD with small time steps and air mesh for surgical simulation International conference

    S. Li, Y. Hayashi, M. Oda, K. Misawa, K. Mori

    CARS 2021  2021.6.23 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  63. Intestine segmentation combining Watershed transformation and machine learning-based distance map estimation International conference

    H. Oda, Y. Hayashi, T. Kitasaka, Y. Tamada, A. Takimoto, A. Hinoki, H. Uchida, K. Suzuki, H. Itoh, M. Oda, K. Mori

    CARS 2021  2021.6.24 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  64. Blood vessel regions segmentation from laparoscopic videos using fully convolutional networks with multi field of view input International conference

    K. Mori, S. Morimitsu, S. Yamamoto, T. Ozawa, T. Kitasaka, Y. Hayashi, M. Oda, M. Ito, N. Takeshita, K. Misawa

    CARS 2021  2021.6.23 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  65. Binary Polyp-Size Classification based on Deep-Learning Estimation of Spatial Information International conference

    H. Itoh, M. Oda, K. Jiang, Y. Mori, M. Misawa, S.- E. Kudo, K. Imai, S. Ito, K. Hotta, K. Mori

    CARS 2021  2021.6.22 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  66. Experimental evaluation of loss functions in YOLO-v3 training for the perforation detection and localization in colonoscopic videos International conference

    K. Jiang, H. Itoh, M. Oda, T. Okumura, Y. Mori, M. Misawa, T. Hayashi, S. E. Kudo, K. Mori

    CARS 2021  2021.6.22 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  67. Aorta-aware GAN for non-contrast to artery contrasted CT translation and its application to abdominal aortic aneurysm detection International conference

    T. Hu, M. Oda, Y. Hayashi, Z. Lu, K. K. Kumamaru, T. Akashi, S. Aoki, K. Mori

    CARS 2021  2021.6.22 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  68. Depth-based branching level estimation for bronchoscopic navigation International conference

    Cheng Wang, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Hirotsugu Takabatake, Masaki Mori, Hirotoshi Honma, Hiroshi Natori , Kensaku Mori

    CARS 2021  2021.6.21 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  69. COVID-19 lung infection and normal region segmentation from CT volumes using FCN with local and global spatial feature encoder International conference

    M. Oda, Y. Hayashi, Y. Otake, M. Hashimoto, T. Akashi, K. Mori

    CARS 2021  2021.6.21 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  70. A cascaded fully convolutional network framework for dilated pancreatic duct segmentation International coauthorship International conference

    C. Shen, H. R. Roth, Y. Hayashi, M. Oda, T. Miyamoto, G. Sato, K. Mori

    CARS 2021  2021.6.21 

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    Event date: 2021.6

    Language:English   Presentation type:Oral presentation (general)  

  71. 深層学習を用いた医用画像処理と画像を超えた応用 Invited

    小田 昌宏

    第60回日本生体医工学会大会  2021.6.17 

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    Event date: 2021.6

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

  72. 深層学習に基づく腎癌領域の自動抽出手法の検討

    趙 武楊, 申 忱, 小田 昌宏, 林 雄一郎, 東田 直樹, 橋本 正弘, 陣崎 雅弘, 森 健策

    電子情報通信学会医用画像研究会  2021.5.17 

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    Event date: 2021.5

    Language:Japanese   Presentation type:Oral presentation (general)  

  73. Watershedを用いた肺マイクロCT像からの肺胞セグメンテーション

    椎名 健, 小田 紘久, 鄭 通, 中村 彰太, 小田 昌宏, 森 健策

    電子情報通信学会医用画像研究会  2021.5.17 

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    Event date: 2021.5

    Language:Japanese   Presentation type:Oral presentation (general)  

  74. Spectral-based Convolutional Graph Neural Networksを用いた腹部動脈領域の血管名自動命名に関する研究

    日比 裕太, 林 雄一郎, 北坂 孝幸, 伊東 隼人, 小田 昌宏, 三澤 一成, 森 健策

    電子情報通信学会医用画像研究会  2021.3.17 

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    Event date: 2021.3

    Language:Japanese   Presentation type:Oral presentation (general)  

  75. MICCAI 2020参加報告 Invited

    斉藤 篤, 小田 昌宏, 大竹 義人, 花岡 昇平, 諸岡 健一, 宮内 翔子, 増谷 佳孝, 申 忱, 森 健策

    電子情報通信学会医用画像研究会  2021.3.17 

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    Event date: 2021.3

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

  76. カスケードCNNによる腹腔鏡動画からの出血領域自動抽出

    山本 翔太, 林 雄一郎, 盛満 慎太郎, 北坂 孝幸, 小田 昌宏, 竹下 修由, 伊藤 雅昭, 森 健策

    電子情報通信学会医用画像研究会  2021.3.17 

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    Event date: 2021.3

    Language:Japanese   Presentation type:Oral presentation (general)  

  77. Contrastive Learningを用いた肺野CT画像からCOVID-19の自動判定

    加藤 聡太, 堀田 一弘, 小田 昌宏, 森 健策, 大竹 義人, 橋本 正弘, 明石 敏昭

    電子情報通信学会医用画像研究会  2021.3.16 

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    Event date: 2021.3

    Language:Japanese   Presentation type:Oral presentation (general)  

  78. AIによる画像解析の基礎と眼科画像解析への応用 Invited

    小田 昌宏

    第85回筑波TOC・第23回茨城県眼科医会フォーラム  2021.2.24 

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    Event date: 2021.2

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:オンライン   Country:Japan  

  79. Unsupervised segmentation of COVID-19 infected lung clinical CT volumes using image inpainting and representation learning International conference

    Tong Zheng, Masahiro Oda, Chenglong Wang, Takayasu Moriya, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  80. Extremely imbalanced subarachnoid hemorrhage detection based on enseNet-LSTM network with class-balanced loss and transfer learning International conference

    Zhongyang Lu, Masahiro Oda, Yuichiro Hayashi, Tao Hu, Hayato Itoh, Takeyuki Watadani, Osamu Abe, Masahiro Hashimoto, Masahiro Jinzaki, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  81. Single-shot three-dimensional reconstruction for colonoscopic image analysis International conference

    Hayato Itoh, Masahiro Oda, Yuichi Mori, Masashi Misawa, Shin-ei Kudo, Kinnichi Hotta, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  82. Bronchial orifice segmentation on bronchoscopic video frames based on generative adversarial depth estimation International conference

    Cheng Wang, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Hirotsugu Takabatake, Masaki Mori, Hirotoshi Honma, Hiroshi Natori, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  83. Intestinal region reconstruction of ileus cases from 3D CT images based on graphical representation and its visualization International conference

    Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Yudai Tamada, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  84. Lung infection and normal region segmentation from CT volumes of COVID-19 cases International conference

    Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  85. Extraction of lung and lesion regions from COVID-19 CT volumes using 3D fully convolutional networks International conference

    Yuichiro Hayashi, Masahiro Oda, Chen Shen, Masahiro Hashimoto, Yoshito Otake, Toshiaki Akashi, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  86. Dense-layerbased YOLO-v3 for detection and localization of colon perforations International conference

    Kai Jiang, Hayato Itoh, Masahiro Oda, Taishi Okumura, Yuichi Mori, Masashi Misawa, Takemasa Hayashi, Shin-Ei Kudo, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  87. Context encoder guided self-supervised siamese depth estimation based on stereo laparoscopic images International conference

    Wenda Li, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

    SPIE Medical Imaging 2021  2021.2.15  SPIE

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    Event date: 2021.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  88. Unpaired Medical Image Translation between Portal-venous Phase and Non-contrast CT Volumes for Multi-organ Segmentation International conference

    Chen Shen, Yuichiro Hayashi, Masahiro Oda, Kazunari Misawa and Kensaku Mori

    IFMIA 2021  2021.1.26 

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    Event date: 2021.1

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  89. 放射線診断における研究トピックスと臨床応用~AI応用の基礎から最前線まで~ Invited

    小田 昌宏

    日本医学物理学会教育セミナー  2020.12.19 

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    Event date: 2020.12

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:オンライン   Country:Japan  

  90. Super Resolution of Chest CT Images Using CycleGAN and Micro CT Image Database International conference

    Tong Zheng, Hirohisa Oda, Masahiro Oda, Shota Nakamura, Hiroshi Natori, Hirotsugu Takabatake, Masaki Mori, Kensaku Mori

    RSNA 2020  2020.11.29 

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    Event date: 2020.11 - 2020.12

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  91. Why AI Misses Small Organs and How to Improve Their Recognition Performances International conference

    Masahiro Oda, Kanako K. Kumamaru, Shigeki Aoki, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori, Masaki Mori

    RSNA 2020  2020.11.29 

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    Event date: 2020.11 - 2020.12

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  92. How Fully Convolutional Networks Trained From Small Amount of Data Using Fine-Tuning in Multi-Organ Segmentation From CT Images? International conference

    Yuichiro Hayashi, Chen Shen, Masahiro Oda, Kazunari Misawa, Kensaku Mori

    RSNA 2020  2020.11.29 

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    Event date: 2020.11 - 2020.12

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  93. Wavelet-Based Fully Convolution Network for Estimating Artery Contrast CT Images From Non-Contrast CT Images International conference

    Tao Hu, Masahiro Oda, Yuichiro Hayashi, Zhongyang Lu, Kanako K. Kumamaru, Shigeki Aoki, Kensaku Mori

    RSNA 2020  2020.11.29 

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    Event date: 2020.11 - 2020.12

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  94. How Does Graphical Convolutional Neural Network Work for Anatomical Labeling of Blood Vessels Extracted From CT Images? International conference

    Kensaku Mori, Yuta Hibi, Yuichiro Hayashi, Masahiro Oda, Kazunari Misawa, Hayato Itoh

    RSNA 2020  2020.11.29 

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    Event date: 2020.11 - 2020.12

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  95. How Spatial Information Embedding Improves Multi-Organ Segmentation From Abdominal CT Images Based on Fully Convolutional Networks International conference

    Chen Shen, Chenglong Wang, Holger R. Roth, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    RSNA 2020  2020.11.29 

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    Event date: 2020.11 - 2020.12

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  96. 腸閉塞およびイレウスの診断支援システムにおける距離マップの導入

    小田 紘久, 林 雄一郎, 北坂 孝幸,玉田 雄大,滝本 愛太朗,檜 顕成, 内田 広夫,鈴木 耕次郎, 伊東 隼人,小田 昌宏,森 健策

    第29回日本コンピュータ外科学会大会  2020.11.22  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  97. シンポジウム③ AI-CASの先に来るもの~現在そしてその先:日常に溶け込む診断と治療 Invited

    小田 昌宏

    第29回日本コンピュータ外科学会大会  2020.11.23  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:オンライン   Country:Japan  

  98. AI入門ワークショップ:AIハンズオンセミナー Invited

    小田 昌宏

    第29回日本コンピュータ外科学会大会  2020.11.23  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:オンライン   Country:Japan  

  99. Preliminary study of Loss-Function Design for Detection and Localization of Perforations with YOLO-v3 in Colonoscopic Images

    凱 蒋, 伊東 隼人,小田 昌宏,奥村 大志,森 悠一,三澤 将史,林 武雅,工藤 進英,森 健策

    第29回日本コンピュータ外科学会大会  2020.11.23  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  100. SUN database : 大腸ポリープ自動検出器の精度評価に向けた試験用画像

    伊東 隼人, 三澤 将史,森 悠一,小田 昌宏,工藤 進英, 森 健策

    第29回日本コンピュータ外科学会大会  2020.11.23  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  101. 気管支鏡ナビゲーションのための敵対的生成による内視鏡画像深度推定の評価

    王 成, 小田 昌宏,林 雄一郎,北坂 孝幸,本間 裕敏,高畠 博嗣,森 雅樹,名取 博, 森 健策

    第29回日本コンピュータ外科学会大会  2020.11.23  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  102. 腹腔鏡動画像用オンラインアノテーションツールの開発

    屠 芸豪, 伊東 隼人,小澤 卓也,小田 昌宏, 竹下 修由,伊藤 雅昭,森 健策

    第29回日本コンピュータ外科学会大会  2020.11.22  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  103. 深層学習によるMRI画像からの神経鞘腫の自動位置検出

    小田 昌宏, 伊藤 定之, 今釜 史郎, 森 健策

    第29回日本コンピュータ外科学会大会  2020.11.22  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  104. 表現学習に基づくクラスタリングによるCOVID-19 肺CT像からの病変部抽出手法

    鄭 通, 小田 昌宏, 王 成龍,林 雄一郎,橋本 正弘, 大竹 義人,明石 敏昭, 森 健策

    第29回日本コンピュータ外科学会大会  2020.11.22  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  105. Dilated convolution を用いた腹腔鏡動画像からの血管領域抽出における空間情報利用に関する検討

    盛満 慎太郎, 山本 翔太, 小澤 卓也, 北坂 孝幸, 林 雄一郎, 小田 昌宏, 伊藤 雅昭, 竹下 修由,三澤 一成, 森 健策

    第29回日本コンピュータ外科学会大会  2020.11.22  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  106. 局所情報に注目した腹腔鏡動画像からの出血領域抽出

    山本 翔太, 盛満 慎太郎,林 雄一郎,北坂 孝幸,小田 昌宏,伊藤 雅昭,竹下 修由, 森 健策

    第29回日本コンピュータ外科学会大会  2020.11.22  日本コンピュータ外科学会

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  107. GANを用いたAIの仕組みと応用 Invited

    小田 昌宏

    第5回Advanced Medical Imaging研究会  2020.11.22 

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:オンライン   Country:Japan  

  108. Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning International conference

    Chen Shen, Pochuan Wang, Holger R Roth, Dong Yang, Daguang Xu, Masahiro Oda, Kazunari Misawa, Po-Ting Chen, Wei-Chih Liao, Kao-Lang Liu, Weichung Wang, Kensaku Mori

    1st MICCAI Workshop on Distributed And Collaborative Learning  2020.10.4 

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    Event date: 2020.10

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  109. Synthetic laparoscopic video generation for machine learning-based surgical International conference

    Yuichiro Hayashi, Takuya Ozawa, Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Nobuyoshi Takeshita, Masaaki Ito , Kensaku Mori

    Joint MICCAI workshop 2020, AE-CAI/CARE/OR2.0  2020.10.4 

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    Event date: 2020.10

    Language:English   Presentation type:Poster presentation  

    Venue:Online  

  110. ハンズオンセミナー3:外科領域における医療用画像の深層学習 Invited

    小田 昌宏

    第14回日本CAOS研究会/第26回日本最小侵襲整形外科学会  2020.9.22 

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    Event date: 2020.9

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:高知医療センター(オンライン)   Country:Japan  

  111. ITテクノロジー2:外科支援におけるAIの現在とこれから Invited

    小田 昌宏

    第14回日本CAOS研究会/第26回日本最小侵襲整形外科学会  2020.9.22 

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:オンライン   Country:Japan  

  112. Preliminary Study of Perforation Detection and Localization for Colonoscopy Video

    Kai Jiang, Hayato Itoh, Masahiro Oda, Taishi Okumura, Yuichi Mori, Masashi Misawa, Takemasa Hayashi, Shin-Ei Kudo, Kensaku Mori

    2020.9.17 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

  113. JAMITハンズオンセミナー Invited

    原武史, 李鎔範, 中田典生, 小田昌宏

    第39回日本医用画像工学会大会  2020.9.17  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:オンライン   Country:Japan  

  114. 腹腔鏡手術動画像データベース構築に向けたリモートアノテーションツールのプロトタイプ開発

    屠 芸豪, 伊東 隼人, 小澤 卓也, 小田 昌宏, 竹下 修由, 伊藤 雅昭, 森 健策

    第39回日本医用画像工学会大会  2020.9.19  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  115. Spatial Information Considered Self-Supervised Depth Estimation Based on Image Pairs from Stereo Laparoscope

    Wenda Li, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

    2020.9.19 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

  116. 大腸内視鏡のための教師なし深度画像推定法における補助タスク検討

    伊東 隼人, 小田 昌宏, 森 悠一, 三澤 将史, 工藤 進英, 堀田 欣一, 高畠 博嗣, 森 雅樹, 名取 博, 森 健策

    第39回日本医用画像工学会大会  2020.9.19  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  117. Preliminary Study on Classification of Hands' Bone Marrow Edema Using X-ray Images

    Dongping Pan, Masahiro Oda, Kou Katayama, Takanobu Okubo, Kensaku Mori

    2020.9.19 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

  118. Unsupervised 3D Super-resolution of Clinical CT Volumes by Utilizing Multi-axis 2D Super-resolution

    Tong Zheng, Hirohisa Oda, Masahiro Oda, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

    2020.9.18 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

  119. Cross-phase CT Image Registration Using Convolutional Neural Network

    Tao Hu, Masahiro Oda, Yuichiro Hayashi, Zhongyang Lu, Kanako Kunishishima Kumamaru, Shigeki Aoki, Kensaku Mori

    2020.9.18 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

  120. 広範囲の隣接関係を考慮したグラフニューラルネットワークを用いた腹部動脈血管名自動命名の検討

    日比 裕太, 林 雄一郎, 北坂 孝幸, 伊東 隼人, 小田 昌宏, 三澤 一成, 森 健策

    第39回日本医用画像工学会大会  2020.9.18  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  121. 大域及び局所情報を用いた深層学習による出血領域自動セグメンテーション

    山本 翔太, 盛満 慎太郎, 林 雄一郎, 北坂 孝幸, 小田 昌宏, 伊藤 雅昭, 竹下 修由, 森 健策

    第39回日本医用画像工学会大会  2020.9.18  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  122. Dilated convolution を用いた FCN による腹腔鏡動画像からの血管領域抽出

    盛満 慎太郎, 山本 翔太, 北坂 孝幸, 林 雄一郎, 小田 昌宏, 竹下 修由, 伊藤 雅昭, 三澤 一成, 森 健策

    第39回日本医用画像工学会大会  2020.9.18  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  123. Preliminary Study on Classification of Interstitial Cystitis Using Cystoscopy Images

    Tao Chu, Masahiro Oda, Akira Furuta, Tokunori Yamamoto, Kensaku Mori

    2020.9.17 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

  124. COVID-19 症例の定量評価のためのCT 像からの肺野自動セグメンテーション

    小田 昌宏, 林 雄一郎, 大竹 義人, 橋本 正弘, 明石 敏昭, 森 健策

    第39回日本医用画像工学会大会  2020.9.17  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  125. A study on Subarachnoid Hemorrhage automatic detection utilized Transfer Learning on extremely imbalanced brain CT datasets

    Zhongyang Lu, Masahiro Oda, Yuichiro Hayashi, Tao Hu, Hayato Ito,Takeyuki Watadani,Osamu Abe,Masahiro Hashimoto,Masahiro Jinzaki,Kensaku Mori

    2020.9.17 

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    Event date: 2020.9

    Language:English   Presentation type:Oral presentation (general)  

  126. 読影レポート解析を利用した医用画像データベースからのアノテーション付きデータセット作成に関する初期検討

    林 雄一郎, 鈴村 悠輝, 岡崎 真治, 小田 昌宏, 森 健策

    第39回日本医用画像工学会大会  2020.9.17  日本医用画像工学会

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン  

  127. An Application of Multi-organ Segmentation from Thick-slice Abdominal CT Volumes using Transfer Learning International conference

    C. Shen, M. Oda, H. Roth, H. Oda, Y. Hayashi, K. Misawa, K. Mori

    CARS 2020  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  128. TinyLoss: loss function for tiny image difference evaluation and its application to unpaired non-contrast to contrast abdominal CT estimation International conference

    Masahiro Oda, T. Hu, K. K. Kumamaru, T. Akashi, S. Aoki, K. Mori

    CARS 2020  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  129. Virtual cleansing by unpaired image translation of intestines for detecting obstruction International conference

    K. Nishio, H. Oda, T. Kitasaka, Y. Tamada, H. Amano, A. Takimoto, K. Chiba, Y. Hayashi, H. Itoh, M. Oda, A. Hinoki, H. Uchida, K. Mori

    CARS 2020  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  130. SR-CycleGAN V2: CycleGAN-based unsupervised superresolution with pixel-shuffling International conference

    T. Zheng, H. Oda, T. Moriya, T. Sugino, S. Nakamura, M. Oda, M. Mori, H. Takabatake, H. Natori, K. Mori

    CARS 2020  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  131. Development of a robust endocytoscopic-image classification method towards the construction of practical CAD system in endocytoscopy - from the viewpoint of generalisation ability for non-specific hospital diagnosis International conference

    H. Itoh, Y. Mori, M. Misawa, S. –E. Kudo, K. Hotta, K. Ohtsuka, S. Saito, Y. Saito, H. Ikematsu, Y. Hayashi, M. Oda, K. Mori

    22nd International Conference on Computer-Aided Diagnosis and Artificial Intelligence (CAD-AI)  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  132. A visual SLAM based bronchoscope tracking scheme for bronchoscopic navigation International conference

    C. Wang, M. Oda, Y. Hayashi, B. Villard, T. Kitasaka, H. Takabatake, M. Mori, H. Honma, H. Natori, K. Mori

    34th International Congress and Exhibition on Computer Assisted Radiology (CAR)  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  133. Detecting ganglion cells on virtual slide images: Macroscopic masking by superpixel International conference

    H. Oda, Y. Tamada, K. Nishio, T. Kitasaka, H. Amano, K. Chiba, A. Hinoki, H. Uchida, M. Oda, K. Mori

    CARS 2020  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  134. Blood vessel segmentation from laparoscopic video using ConvLSTM U-Net International conference

    S. Morimitsu, S. Yamamoto, T. Ozawa, T. Kitasaka, Y. Hayashi, M. Oda, M. Ito, N. Takeshita, K. Misawa, K. Mori

    CARS 2020  2020.6.23 

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    Event date: 2020.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online  

  135. Symposium6, Japan Medical Imaging Database: AI image analysis based on massive data in J-MID Invited

    小田 昌宏

    第79回日本医学放射線学会総会web  2020.5.15  日本医学放射線学会

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    Event date: 2020.5 - 2020.6

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:オンライン   Country:Japan  

  136. Automated eye disease classification method from anterior eye image using anatomical structure focused image classification technique International conference

    Masahiro Oda, Naoyuki Maeda, Takefumi Yamaguchi, Hideki Fukuoka, Yuta Ueno, Kensaku Mori

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE  2020.2.17  SPIE

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Country:United States  

    DOI: 10.1117/12.2549951

    Scopus

  137. Organ segmentation from full-size CT images using memory-efficient FCN International conference

    Chenglong Wang, Masahiro Oda, Kensaku Mori

    SPIE Medical Imaging 2020  2020.2.16 

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Texus, USA   Country:United States  

  138. Spatial information-embedded fully convolutional networks for multi-organ segmentation with improved data augmentation and instance normalization International conference

    Chen Shen, Chenglong Wang, Holger R. Roth, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    SPIE Medical Imaging 2020  2020.2.19 

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Texus, USA   Country:United States  

  139. Improved visual SLAM for bronchoscope tracking and registration with pre-operative CT images International conference

    Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Takayuki Kitasaka, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    SPIE Medical Imaging 2020  2020.2.18 

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Texus, USA   Country:United States  

  140. Usefulness of fine-tuning for deep learning based multi-organ regions segmentation method from non-contrast CT volumes using small training dataset International conference

    Yuichiro Hayashi, Chen Shen, Holger R. Roth, Masahiro Oda, Kazunari Misawa, Masahiro Jinzaki, Masahiro Hashimoto, Kanako K. Kumamaru, Shigeki Aoki, Kensaku Mori

    SPIE Medical Imaging 2020  2020.2.17 

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Texus, USA   Country:United States  

  141. Visualising decision-reasoning regions in computer-aided pathological pattern diagnosis of endoscytoscopic images based on CNN weights analysis International conference

    Hayato Itoh, Zhongyang Lu, Yuichi Mori, Masashi Misawa, Masahiro Oda, Shin-ei Kudo, Kensaku Mori

    SPIE Medical Imaging 2020  2020.2.17 

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Texus, USA   Country:United States  

  142. Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images International conference

    Hirohisa Oda, Kohei Nishio, Takayuki Kitasaka, Hizuru Amano, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, Kensaku Mori

    SPIE Medical Imaging 2020  2020.2.17 

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Texus, USA   Country:United States  

  143. Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database International conference

    Tong Zheng, Hirohisa Oda, Takayasu Moriya, Takaaki Sugino, Shota Nakamura, Masahiro Oda, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

    SPIE Medical Imaging 2020  2020.2.17 

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    Event date: 2020.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Texus, USA   Country:United States  

  144. 深層学習時代の医用画像処理におけるデータと計算環境 Invited

    小田 昌宏

    PCCC19「来たるべきSociety 5.0時代に向けて」(第19回PCクラスタシンポジウム)  2019.12.13 

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    Event date: 2019.12

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    researchmap

  145. Generative Adversarial Networks Showcase: Their Mechanisms and Radiological Applications International conference

    Masahiro Oda, Hirohisa Oda, Kanako K. Kumamaru, Shigeki Aoki, Hiroshi Natori, Kensaku Mori, Masaki Mori, Hirotsugu Takabatake

    Radiological Society of North America (RSNA) 2019 

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    Event date: 2019.12

    Language:English   Presentation type:Poster presentation  

    Venue:Chicago, USA   Country:United States  

  146. Realistic virtual endoscopic image generation method using image domain translation

    Masahiro Oda,Kiyohito Tanaka,Hirotsugu Takabatake,Masaki Mori, Hiroshi Natori,Kensaku Mori

    The 28th Annual Congress of Japan Society of Computer Aided Surgery 

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    Event date: 2019.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:University of Tokyo   Country:Japan  

    We propose a realistic virtual endoscopic image generation method for endoscope simulators. Endoscope simulators are used to train endoscopists. However, less realistic visualization of simulators reduces effect of training. Main differences of virtual endoscopic images generated by simulators and real endoscopic images are textures and light reflections on the surface of organs. The differences should be reduced to improve reality of virtual images. This paper proposes a method to improve reality of virtual endoscopic images using a virtual to real endoscopic image domain translation technique. In the image domain translation, the structure of fully convolutional network (FCN) that performs image translation has relation to the reality of translated images. We experimentally confirmed reality of translated images using three different FCNs. From the result, use of larger numbers of kernels and layers resulted in generation of realistic images.

  147. 深層学習を用いた医用画像処理研究の最前線 Invited

    小田 昌宏

    第47回日本放射線技術学会秋季学術大会(第86回画像部会 教育講演) 

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    Event date: 2019.10

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:グランキューブ大阪   Country:Japan  

  148. JAMITハンズオンセミナー

    原武史, 中田典生, 小田昌宏, 福岡大輔, 田中理恵, 中山良平

    第38回日本医用画像工学会大会 

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    Event date: 2019.7

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:奈良春日野国際フォーラム 甍~ I・RA・KA ~   Country:Japan  

  149. Estimation of Contrasted Abdominal CT Volume from Non-contrasted CT Volume using Generative Adversarial Frameworks

    Masahiro Oda, Kanako Kumamaru, Shigeki Aoki, Kensaku Mori

    The 38th JAMIT Annual Meeting 

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    Event date: 2019.7

    Language:Japanese   Presentation type:Poster presentation  

    Venue:Nara Kasugano International Forum   Country:Japan  

    We propose an estimation method of an abdominal contrasted CT volume from a non-contrasted CT volume. In diagnosis and treatment, contrasted CT volumes are taken to confirm anatomical structure and abnormal regions related to the blood vessels. However, administration of contrast agents causes dyspnea and cardiac arrest in some cases. In this paper, we propose an estimation method of contrasted images from non-contrasted images in abdominal CT volumes. As the estimation method, we employ an image regression model using a fully convolutional network (FCN). We trained the FCN in a direct-training and indirect-trainings using generative adversarial frameworks (pix2pix, CycleGAN). In our experiments using abdominal CT volumes, contrasted CT-like volumes having good-quality were generated when we used the CycleGAN.

  150. Non-contrast to contrasted abdominal CT volume regression using fully convolutional network International conference

    Masahiro Oda, Kanako K. Kumamaru, Shigeki Aoki, Kensaku Mori

    Computer Assisted Radiology and Surgery (CARS) 2019 

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    Event date: 2019.6

    Language:English   Presentation type:Poster presentation  

    Venue:Rennes, France   Country:France  

  151. AI and Machine Learning in Medical Image Engineering Invited

    Masahiro Oda

    The 63rd Annual Conference of the Institute of Systems, Control and Information Engineers (SCI'19) 

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    Event date: 2019.5

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:Central Electric Club   Country:Japan  

    In the medical image processing field, utilization of AI and machine learning techniques are getting popular. Among AI and machine learning techniques, the deep learning significantly contributes to improve performances of medical image processing methods. This paper introduces some automated segmentation and lesion detection techniques including conventional and deep learning-based methods. Improvements of their performances obtained by using deep learning techniques are also presented. Additionally, two problems that medical image processing researches who use AI and machine learning techniques facing are introduced.

  152. Development of AI assisted diagnosis and treatment powered by integrated use of various data Invited

    Masahiro Oda

    The 92th Annual Meeting of the Japan Orthopaedic Association 

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    Event date: 2019.5

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:Pacifico Yokohama   Country:Japan  

  153. AIプログラミング基礎編,AIプログラミング実践編 Invited

    小田昌宏

    えひめAI・IoT研究会技術セミナー 

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    Event date: 2019.4

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:愛媛大学   Country:Japan  

  154. AIを活用した画像処理について Invited

    小田 昌宏

    えひめAI・IoT研究会技術セミナー 

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    Event date: 2019.4

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:愛媛大学   Country:Japan  

  155. Colonoscope tracking method based on shape estimation network International conference

    Masahiro Oda, Holger R. Roth, Takayuki Kitasaka, Kazuhiro Furukawa, Yoshiki Hirooka, Nassir Navab, Kensaku Mori

    SPIE Medical Imaging 2019 

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    Event date: 2019.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:San Diego, California, USA   Country:United States  

    This paper presents a colonoscope tracking method utilizing a colon shape estimation method. CT colonography is used as a less-invasive colon diagnosis method. If colonic polyps or early-stage cancers are found, they are removed in a colonoscopic examination. In the colonoscopic examination, understanding where the colonoscope running in the colon is difficult. A colonoscope navigation system is necessary to reduce overlooking of polyps. We propose a colonoscope tracking method for navigation systems. Previous colonoscope tracking methods caused large tracking errors because they do not consider deformations of the colon during colonoscope insertions. We utilize the shape estimation network (SEN), which estimates deformed colon shape during colonoscope insertions. The SEN is a neural network containing long short-term memory (LSTM) layer. To perform colon shape estimation suitable to the real clinical situation, we trained the SEN using data obtained during colonoscope operations of physicians. The proposed tracking method performs mapping of the colonoscope tip position to a position in the colon using estimation results of the SEN. We evaluated the proposed method in a phantom study. We conrmed that tracking errors of the proposed method was enough small to perform navigation in the ascending, transverse, and descending colons.

    DOI: 10.1117/12.2512729

  156. Report on MICCAI 2018

    Masahiro Oda, Yoshito Otake, Hayato Itoh, Takaaki Sugino, Atsushi Saito, Ryo Furukawa, Takashi Onishi, Atsushi Imiya, Kensaku Mori

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    Event date: 2019.1

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

    In this paper, the outlines of MICCAI 2018 main conference sessions and workshops are introduced. A few interesting reports in the conference are also introduced and explained.

  157. Deep Learning Sample Code Collection for Medical Image Processing: DMED

    Masahiro Oda, Takeshi Hara, Kensaku Mori

    The 27th Annual Congress of Japan Society of Computer Aided Surgery 

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    Event date: 2018.11

    Language:Japanese   Presentation type:Poster presentation  

    Country:Japan  

    Deep learning techniques are widely used in both of computer aided surgery (CAS) and diagnosis (CAD) fields. Many software to use deep learning are available. However, in the medical assisting research field, we need to implement new deep learning-based methods. It is difficult for researchers who are not specialized in image processing or machine learning. To accelerate use of deep learning for all researchers, we developed the deep learning sample code collection for medical image processing (DMED). DMED enables easy use of key deep learning-based methods including medical image processing. Current DMED includes sample codes for image classification, segmentation, and superresolution. Different from the previous deep learning library such as the NiftyNet and the DLTK, the DMED performs training processes in reasonable processing time without GPU. We expect the DMED accelerates use of deep learning-based image processing methods in the CAS and CAD fields.

  158. Deep learning for medical images in surgical field

    Masahiro Oda

    The 27th Annual Congress of Japan Society of Computer Aided Surgery 

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    Event date: 2018.11

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Country:Japan  

    Deep learning contributes growing of the information processing field. It is used to achieve computer systems having high recognition performances. Traditionally, recognition algorithm was individually developed for each task. In contrast to them, a common model or a framework is applicable to many recognition tasks in the deep learning field. This property contributes acceleration of research and development. In this session, we explain how to perform image processing using deep learning in hands-on style. How to develop and execute basic deep learning-based image processing methods including image classification and segmentation are explained. Programs of these methods will run on attendee's computers. Attendee are requested to install software and download data to their own computers prior to joining the hands-on.

  159. AIによるコンピュータ外科の始め方 - 研究環境構築法 Invited

    小田 昌宏

    第27回日本コンピュータ外科学会大会 

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    Event date: 2018.11

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:奈良県文化会館   Country:Japan  

  160. Colon Shape Estimation Method for Colonoscope Tracking using Recurrent Neural Networks International conference

    Masahiro Oda, Holger Roth, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Nassir Navab, Kensaku Mori

    MICCAI 2018 

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    Event date: 2018.9

    Language:English   Presentation type:Poster presentation  

    Venue:Granada, Spain   Country:Spain  

  161. 深層学習を用いた医用画像処理の始め方 Invited

    小田昌宏

    生体医工学シンポジウム2018 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:名古屋工業大学   Country:Japan  

  162. Tutorial of Deep Learning

    Masahiro Oda

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    Event date: 2018.9

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:Nagoya Institute of Technology   Country:Japan  

  163. 医用画像における深層学習を利用した研究のはじめかた Invited

    小田昌宏

    第37回日本医用画像工学大会 

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    Event date: 2018.7

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:筑波大学 天王台キャンパス 大学会館   Country:Japan  

  164. Fully convolutional networkを用いた小構造物セグメンテーション方法の検討及び腹部動脈への適用

    小田昌宏, Holger R. Roth, 北坂孝幸, 三澤一成, 藤原道隆, 森健策

    第37回日本医用画像工学大会(JAMIT2018) 

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    Event date: 2018.7

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:筑波大学 天王台キャンパス 大学会館   Country:Japan  

  165. Hands-on Seminar on JAMIT

    Norio Nanata, Takeshi Hara, Masahiro Oda, Daisuke Fukuoka

    The 37th JAMIT Annual Meeting 

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    Event date: 2018.7

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:University of Tsukuba   Country:Japan  

  166. Abdominal artery segmentation from CT volumes using fully convolutional network for small artery segmentation International conference

    Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori

    Computer Assisted Radiology and Surgery (CARS) 2018 

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    Event date: 2018.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Berlin, Germany   Country:Germany  

  167. 機械学習を用いた診断と治療支援 Invited

    小田 昌宏

    第47回日本脊椎脊髄病学会学術集会 

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    Event date: 2018.4

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Venue:神戸   Country:Japan  

  168. Machine learning-based colon deformation estimation method for colonscope tracking International conference

    Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Nassir Navab, Kensaku Mori

    SPIE Medical Imaging 

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    Event date: 2018.2

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Marriott Marquis Houston,Houston, Texas, USA   Country:United States  

  169. Machine Learning Techniques for Automated Accurate Organ Segmentation and Their Applications to Diagnosis Assistance International conference

    Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori, Michitaka Fujiwara, Daniel Rueckert

    RSNA 2017 (Radiological Society of North America) 

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    Event date: 2017.11 - 2017.12

    Language:English   Presentation type:Poster presentation  

    Venue:McCormick Place, Chicago, USA   Country:United States  

  170. 大腸内視鏡トラッキングのためのregression forestsを用いた大腸変形モデルの開発

    小田昌宏,北坂孝幸,古川和宏,宮原良二,廣岡芳樹,後藤秀実,Nassir Navabe, 森 健策

    第26回日本コンピュータ外科学会大会(JSCAS2017) 

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    Event date: 2017.10

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:名古屋大学 東山キャンパス 豊田講堂・シンポジオン)   Country:Japan  

  171. AIによるコンピューター手術支援研究の加速 Invited

    小田 昌宏

    第26回日本コンピュータ外科学会大会(JSCAS2017) 

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    Event date: 2017.10

    Language:Japanese   Presentation type:Oral presentation (invited, special)  

    Country:Japan  

  172. 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation International conference

    Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken'ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori

    MICCAI 2017, 3rd Workshop on Deep Learning in Medical Image Analysis 

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    Event date: 2017.9

    Language:English   Presentation type:Poster presentation  

    Venue:Quebec, Canada   Country:Canada  

  173. CT 像から抽出した腹部動脈領域におけるCNN を用いた過検出削減でのパッチ画像生成手法の検討

    小田 昌宏, 山本 徳則, 吉野 能, 森 健策

    第36回日本医用画像工学会大会(JAMIT2017) 

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    Event date: 2017.7

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:じゅうろくプラザ 岐阜市   Country:Japan  

  174. False positive reduction of abdominal artery segmentation from CT volumes based on deep convolutional neural networks International conference

    Masahiro Oda, Tokunori Yamamoto, Yasushi Yoshino, Kensaku Mori

    Computer Assisted Radiology and Surgery (CARS) 2017 

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    Event date: 2017.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:NH Collection Barcelona Constanza, Barcelona, Spain   Country:Spain  

  175. Endocytoscope image classification using deep convolutional neural networks International conference

    Masahiro Oda, Yutaka Hoshiyama, Masashi Misawa, Yuichi Mori, Kenichi Takeda, Sin-ei Kudo, Kensaku Mori

    Computer Assisted Radiology and Surgery (CARS) 2017 

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    Event date: 2017.6

    Language:English   Presentation type:Oral presentation (general)  

    Venue:NH Collection Barcelona Constanza, Barcelona, Spain   Country:Spain  

  176. 大腸変形モデルを用いた大腸内視鏡下治療誘導システムの開発 Invited

    小田 昌宏

    第31回人工知能学会全国大会 

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    Event date: 2017.5

    Language:Japanese   Presentation type:Symposium, workshop panel (nominated)  

    Venue:ウインクあいち   Country:Japan  

  177. Extraction of membrane structure in eyeball from MR volumes International conference

    Masahiro Oda, Kin Taichi, Kensaku Mori

    SPIE Medical Imaging, 2017 

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    Event date: 2017.2

    Language:English   Presentation type:Poster presentation  

    Venue:Renaissance Orland at SeaWorld, Orland, Florida, US   Country:Japan  

  178. MICCAI 2016参加報告

    小田 昌宏, 宮内 翔子, 諸岡 健一, 周 向栄, 増谷 佳孝, 中口 俊哉, 井宮 淳, 森 健策

    電子情報通信学会医用画像研究会 

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    Event date: 2017.1

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  179. Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation International conference

    Masahiro Oda, Natsuki Shimizu, Kenichi Karasawa, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, and Kensaku Mori

    MICCAI 2016 

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    Event date: 2016.10

    Language:English   Presentation type:Poster presentation  

    Venue:Intercontinental Atheneum, Athens, Greece   Country:Greece  

  180. Segmentation method of abdominal arteries from CT volumes utilizing intensity transition along arteries International conference

    Masahiro Oda, Tokunori Yamamoto, Yasushi Yoshino, Kensaku Mori

    Computer Assisted Radiology and Surgery (CARS) 2016 

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    Event date: 2016.6

    Language:English   Presentation type:Poster presentation  

    Venue:Heidelberg Convention Center, Heidelberg, Germany   Country:Germany  

  181. Position-based adjustment of landmark based correspondence finding in electromagnetic sensor-based colonoscope tracking method International conference

    Masahiro Oda, Hiroaki Kondo, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Nassir Navab, and Kensaku Mori

    SPIE Medical Imaging, 2016 

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    Event date: 2016.2 - 2016.3

    Language:English   Presentation type:Oral presentation (general)  

    Venue: Town & Country Resort and Convention Center, San Diego, California, USA   Country:United States  

  182. 磁気式位置センサを用いた大腸内視鏡トラッキング手法の精度解析

    小田 昌宏, 近藤 弘明, 北坂 孝幸, 古川 和宏, 宮原 良二, 廣岡 芳樹, 後藤 秀美, Nassir Navab, 森 健策

    第24回日本コンピュータ外科学会大会 

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    Event date: 2015.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:東京大学 本郷キャンパス   Country:Japan  

  183. Tracking Accuracy Evaluation of Electromagnetic Sensor-based Colonoscope Tracking Method International conference

    Masahiro Oda, Hiroaki Kondo, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Y. Hirooka, Hidemi Goto, Nassir Navab, and Kensaku Mori

    2nd International Workshop on Computer-Assisted and Robotic Endoscopy at MICCAI 2015 

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    Event date: 2015.10

    Language:English   Presentation type:Oral presentation (general)  

    Country:Germany  

  184. 局所的濃度値情報を利用したCT像からの血管抽出手法の改善 International conference

    小田 昌宏, 加賀城 充, 山本 徳則, 吉野 能, 森 健策

    第34回日本医用画像工学会大会 

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    Event date: 2015.7 - 2015.8

    Language:Japanese   Presentation type:Poster presentation  

    Venue:金沢歌劇座   Country:Japan  

  185. マイクロCTと3Dプリンタを利用した肺微細構造拡大再現法に関する検討 International conference

    小田 昌宏, 本間 裕敏, 高畠 博嗣, 森 雅樹, 名取 博, 森 健策

    第34回日本医用画像工学会大会 

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    Event date: 2015.7 - 2015.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:金沢歌劇座   Country:Japan  

  186. マイクロCTと3Dプリンタによる肺微細構造拡大再現モデルの作成に関する検討

    小田 昌宏, 本間 裕敏, 高畠 博嗣, 森 雅樹, 名取 博, 森 健策

    電子情報通信学会医用画像研究会 

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    Event date: 2015.7

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:函館市勤労者総合福祉センター   Country:Japan  

  187. Size-by-size iterative segmentation method of blood vessels from CT volumes and its application to renal vasculature International conference

    Masahiro Oda, Mituru Kagajo, Tokunori Yamamoto, Yasushi Yoshino, and Kensaku Mori

    Computer Assisted Radiology and Surgery (CARS) 2015 

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    Event date: 2015.6

    Language:English   Presentation type:Poster presentation  

    Country:Spain  

  188. 反復抽出処理を用いた造影CT像からの血管抽出手法の開発

    小田 昌宏, 加賀城 充, 山本 徳則, 吉野 能, 森 健策

    電子情報通信学会医用画像研究会 

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    Event date: 2015.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:石垣島 ホテルミヤヒラ   Country:Japan  

  189. Connection method of separated luminal regions of intestine from CT volumes International conference

    Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Osamu Watanabe, Takafumi Ando, Yoshiki Hirooka, Hidemi Goto, and Kensaku Mori

    SPIE Medical Imaging 2015 

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    Event date: 2015.2

    Language:English   Presentation type:Oral presentation (general)  

    Country:United States  

  190. Automated branching pattern report generation for laparoscopic surgery assistance International conference

    Masahiro Oda, Tetsuro Matsuzaki, Yuichiro Hayashi, Takayuki Kitasaka, Kazunari Misawa and Kensaku Mori

    SPIE Medical Imaging 2015 

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    Event date: 2015.2

    Language:English   Presentation type:Oral presentation (general)  

    Country:United States  

  191. Automated method for reconstructing fragmented luminal regions of intestine International conference

    Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Osamu Watanabe, Takafumi Ando, Yoshiki Hirooka, Hidemi Goto, and Kensaku Mori

    MICCAI 2014 Workshop on Abdominal Imaging: Computational and Clinical Applications 

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    Event date: 2014.9

    Language:English   Presentation type:Poster presentation  

    Country:United States  

  192. An automated method for connecting separated luminal regions of intestine segmented from CT volumes International conference

    Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Osamu Watanabe, Takafumi Ando, Yoshiki Hirooka, Hidemi Goto, Kensaku Mori

    CARS 2014 

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    Event date: 2014.6

    Language:English   Presentation type:Oral presentation (general)  

    Country:Japan  

  193. Colonoscope navigation system using colonoscope tracking method based on line registration International conference

    Masahiro Oda, Hiroaki Kondo, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Nassir Navab, and Kensaku Mori

    SPIE Medical Imaging 

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    Event date: 2014.2

    Language:English   Presentation type:Poster presentation  

    Country:United States  

  194. Diagnosis and Surgical Assistance by Medical Image Processing International conference

    Masahiro Oda

    ACPR 2013 Tutorial on Pattern Recognition for Medical Augmented Reality Systems 

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    Event date: 2013.11

    Language:English   Presentation type:Oral presentation (keynote)  

    Country:Japan  

  195. Semi-automated Virtual Unfolded View Generation Method of Stomach from CT Volumes International conference

    Masahiro Oda, Tomoaki Suito, Yuichiro Hayashi, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Gen Iinuma, Kazunari Misawa, Shigeru Nawano, and Kensaku Mori

    MICCAI 2013 

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    Event date: 2013.9

    Language:English   Presentation type:Poster presentation  

    Country:Japan  

  196. 大腸内視鏡ナビゲーションシステムにおける大腸内視鏡先端位置推定精度評価

    小田 昌宏, 近藤 弘明, 北坂 孝幸, 古川 和宏, 宮原 良二, 廣岡 芳樹, 後藤 秀実, Nassir Navab, 森 健策

    第22回日本コンピュータ外科学会大会 

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    Event date: 2013.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:東京大学   Country:Japan  

  197. 展開外力自動決定を用いたCT像からの胃仮想展開生成手法

    小田 昌宏, 水藤 倫彰, 林 雄一郎, 北坂 孝幸, 古川 和宏, 宮原 良二, 廣岡 芳樹, 後藤 秀実, 飯沼 元, 三澤 一成, 縄野 繁, 森 健策

    第32回日本医用画像工学会大会 

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    Event date: 2013.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:日本科学未来館/産業技術総合研究所 臨海副都心産学官連携センター   Country:Japan  

  198. Evaluation of automated incision line determination process for unfolded view generation from CT volumes International conference

    Masahiro Oda, Tomoaki Suito, Yuichiro Hayashi, Gen Iinuma, Koichi Furukawa, Kazunari Misawa, Shigeru Nawano, Takayuki Kitasaka, and Kensaku Mori

    CARS 2013 

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    Event date: 2013.6

    Language:English   Presentation type:Oral presentation (general)  

    Country:Germany  

  199. Colonoscope tracking method based on line registration using CT images and electromagnetic sensors International conference

    Masahiro Oda, Burak Acar, Kazuhiro Furukawa, Takayuki Kitasaka, Yasuhito Suenaga, Nassir Navab, and Kensaku Mori

    CARS 2013 

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    Event date: 2013.6

    Language:English   Presentation type:Poster presentation  

    Country:Germany  

  200. Supine and prone registration of the colon for CT colonography based on dynamic programming technique International conference

    Masahiro Oda, Eiichiro Fukano, Takayuki Kitasaka, Tetsuji Takayama, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Shigeru Nawano, and Kensaku Mori

    SPIE Medical Imaging 

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    Event date: 2013.2

    Language:English   Presentation type:Poster presentation  

    Country:United States  

  201. CAD System for Diagnosis of Stomach Cancer Metastasis Based on Automated Enlarged Lymph Node Detection International conference

    Masahiro Oda, Takayuki Kitasaka, Michitaka Fujiwara, Kazunari Misawa, and Kensaku Mori

    Radiological Society of North America 

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    Event date: 2012.11

    Language:English   Presentation type:Poster presentation  

    Country:United States  

  202. Method for detecting enlarged lymph nodes from 3D abdominal CT images with a multi-shape and multi-scale ellipsoidal structure detection filter International conference

    Masahiro Oda, Takayuki Kitasaka, Michitaka Fujiwara, Kazunari Misawa, and Kensaku Mori

    Abdominal Imaging 2012, 4th International Workshop Held in Conjunction with MICCAI 2012 

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    Event date: 2012.10

    Language:English   Presentation type:Poster presentation  

    Country:France  

  203. 3次元腹部CT像からの腸管潰瘍検出における過検出削減処理の検討

    小田 昌宏, 朝倉 詩穂, 古川 和宏, 北坂 孝幸, 渡辺 修, 安藤 貴文, 後藤 秀実, 森 健策

    第31回日本医用画像工学会大会 

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    Event date: 2012.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:北海道厚生連 札幌厚生病院   Country:Japan  

  204. A gastric lymph node detection method from 3D abdominal CT images using a multi-shape and multi-scale ellipsoidal structure detection filter International conference

    Masahiro Oda, Takayuki Kitasaka, Michitaka Fujiwara, Kazunari Misawa, and Kensaku Mori

    Computer Assisted Radiology and Surgery (CARS) 2012 

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    Event date: 2012.6

    Language:English   Presentation type:Oral presentation (general)  

    Country:Italy  

  205. Automated anatomical labeling method for abdominal arteries extracted from 3D abdominal CT images International conference

    Masahiro Oda, Bui Huy Hoang, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori

    SPIE Medical Imaging 

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    Event date: 2012.2

    Language:English   Presentation type:Poster presentation  

    Country:United States  

  206. Evaluation of deformation accuracy of a virtual pneumoperitoneum method based on clinical trials for patient-specific laparoscopic surgery simulator International conference

    Masahiro Oda, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

    SPIE Medical Imaging 

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    Event date: 2012.2

    Language:English   Presentation type:Oral presentation (general)  

    Country:United States  

  207. 複数形状に対応した楕円体検出フィルタを用いた3次元腹部CT像からのリンパ節検出手法

    小田 昌宏, 北坂 孝幸, 藤原 道隆, 三澤 一成, 森 健策

    電子情報通信学会医用画像研究会 

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    Event date: 2012.1

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:那覇市,沖縄県   Country:Japan  

  208. CAD System for Crohns Disease with Automated Ulcer Detection International conference

    Masahiro Oda, Kazuhiro Furukawa, Takayuki Kitasaka, Osamu Watanabe, Takafumi Ando, Kensaku Mori, Hidemi Goto

    Radiological Society of North America 

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    Event date: 2011.11 - 2011.12

    Language:English   Presentation type:Poster presentation  

    Country:United States  

  209. 局所濃淡構造解析に基づく楕円体検出フィルタによる腹部CT像からのリンパ節検出手法

    小田 昌宏, 北坂 孝幸, 藤原 道隆, 三澤 一成, 森 健策

    第20回日本コンピュータ外科学会大会 

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    Event date: 2011.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:慶應義塾大学理工学部矢上キャンパス   Country:Japan  

  210. Organ segmentation from 3D abdominal CT images based on atlas selection and graph cut International conference

    Masahiro Oda, Teruhisa Nakaoka, Takayuki Kitasaka, Kazuhiro Furukawa, Kazunari Misawa, Michitaka Fujiwara, and Kensaku Mori

    MICCAI 2011 Workshop: Computational and Clinical Applications in Abdominal Imaging 

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    Event date: 2011.9

    Language:English   Presentation type:Oral presentation (general)  

    Country:Canada  

  211. 3次元腹部CT像を用いたクローン病診断支援における潰瘍検出手法の開発

    小田 昌宏, 古川 和宏, 北坂 孝幸, 渡辺 修, 安藤 貴文, 後藤 秀実, 森 健策

    電子情報通信学会医用画像研究会 

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    Event date: 2011.7

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:北海道大学   Country:Japan  

  212. Crohn's disease CAD sysytem with automated ulcer detection International conference

    Masahiro Oda, Kazuhiro Furukawa, Takayuki Kitasaka, Osamu Watanabe, Takafumi Ando, Hidemi Goto, and Kensaku Mori

    3rd CADdemo@CARS Demonstration Workshop on Computer-Aided Detection and Diagnosis 

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    Event date: 2011.6

    Language:English   Presentation type:Oral presentation (general)  

    Country:Germany  

  213. Detection of ulcers based on roughness value from fecal tagging CT image International conference

    Masahiro Oda, Kazuhiro Furukawa, Osamu Watanabe, Takafumi Ando, Hidemi Goto, and Kensaku Mori

    CARS 

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    Event date: 2011.6

    Language:English   Presentation type:Oral presentation (general)  

    Country:Germany  

  214. Detection of longitudinal ulcer using roughness value for computer aided diagnosis of Crohn's disease International conference

    Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Osamu Watanabe, Takafumi Ando, Hidemi Goto, and Kensaku Mori

    SPIE Medical Imaging 

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    Event date: 2011.2

    Language:English   Presentation type:Oral presentation (general)  

    Country:United States  

  215. Development of laparoscopic surgery planning system and its evaluation based on surgery International conference

    Masahiro Oda, Kazuhiro Furukawa, Takayuki Kitasaka, Osamu Watanabe, Takafumi Ando, Kensaku Mori, and Hidemi Goto

    International Forum on Medical Imaging in Asia 

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    Event date: 2011.1

    Language:English   Presentation type:Oral presentation (general)  

    Country:Japan  

  216. CAD system for inflammatory bowel disease using CT images with automated lesion detection and virtual unfolded views International conference

    Radiological Society of North America (RSNA) 2010 

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    Event date: 2010.11

    Language:English   Presentation type:Oral presentation (general)  

  217. Detection of Longitudinal Ulcers Based on Roughness Value from CT Image for Computer Aided Diagnosis and Surgery of Crohn's Disease

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    Event date: 2010.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  218. Synchronized Display of Virtual Colonoscopic Views in Supine and Prone CT Images International conference

    13th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2010) 

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    Event date: 2010.9

    Language:English   Presentation type:Oral presentation (general)  

  219. Development of computer-aided diagnosis system for Crohn's disease using virtual unfolded views International conference

    Computer Assisted Radiology and Surgery (CARS) 2010 

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    Event date: 2010.6

    Language:English   Presentation type:Oral presentation (general)  

  220. 医用画像を用いた大腸がんの計算機支援診断

    小田 昌宏, 北坂 孝幸, 末永 康仁, 森 健策

    画像応用技術専門委員会 

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    Event date: 2010.5

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  221. CT画像に基づく腹腔鏡手術シミュレータによる手術計画立案支援

    小田 昌宏, 森 浩起, 江種 友彦, 北坂 孝幸, 三澤 一成, 森 健策

    第4回Open MRI研究会 

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    Event date: 2010.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Country:Japan  

  222. Development of CAD prototype system for Crohn's disease International conference

    SPIE Medical Imaging 2010 

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    Event date: 2010.2

    Language:English   Presentation type:Poster presentation  

  223. Development of computer aided diagnosis system for Crohn's disease based on concave region detection from 3D abdominal CT images

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    Event date: 2010.1

    Language:Japanese   Presentation type:Poster presentation  

    Country:Japan  

  224. CAD system with synchronized display of supine and prone virtual unfolded views for assisting CT colonograph reading International conference

    Radiological Society of North America (RSNA) 2009 

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    Event date: 2009.11

    Language:English   Presentation type:Oral presentation (general)  

  225. A Prototype Development of Computer Aided Diagnosis System using Virtual Unfolded Views for Crohn's Disease