Updated on 2023/10/11

写真a

 
MORI, Kensaku
 
Organization
Graduate School of Informatics Department of Intelligent Systems 2 Professor
Graduate School
Graduate School of Information Science
Graduate School of Informatics
Undergraduate School
School of Informatics Department of Computer Science
Title
Professor
Contact information
メールアドレス
External link

Degree 1

  1. 博士(工学)

Research Interests 2

  1. Image processing, high-dimensional image processing, pattern recognition, machine learning, medical image processing, computer assisted surgery, computer aided diagnosis, artificial intelligence

  2. artificial intelligence

Research Areas 3

  1. Others / Others  / Visual Information Processing

  2. Others / Others  / Medical Systems

  3. Others / Others  / Intelligent Informatics

Current Research Project and SDGs 1

  1. Study on 3-D image processing and its medical applications

Research History 11

  1. Nagoya University   Administrative Support Organizations

    2017.4

  2. Nagoya University   Information Technology Center   Director in General

    2016.4

  3. Nagoya University   Administrative Support Organizations Information Strategy Office   Head

    2016.4

  4. Nagoya University   Graduate School of Information Science Department of Media Science Intelligent Media Engineering   Professor

    2009.10 - 2017.3

  5. Associate Professor, Dept. of Media Science, Graduate School of Information Science, Nagoya University

    2007.4

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    Country:Japan

  6. Associate Professor, Dept. of Media Science, Graduate School of Information Science, Nagoya University

    2003.4 - 2007.3

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    Country:Japan

  7. 名古屋大学難処理人工物研究センター助教授

    2001.4 - 2003.3

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    Country:Japan

  8. 名古屋大学大学院工学研究科計算理工学専攻講師

    2000.4 - 2001.3

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    Country:Japan

  9. 名古屋大学大学院工学研究科計算理工学専攻助手

    1997.4 - 2000.3

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    Country:Japan

  10. 日本学術振興会特別研究員(PD)

    1996.10

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    Country:Japan

  11. 日本学術振興会特別研究員(DC1)

    1994.4

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    Country:Japan

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Education 3

  1. Nagoya University   Graduate School, Division of Engineering

    1994.4 - 1996.9

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    Country: Japan

  2. Nagoya University   Graduate School, Division of Engineering

    1992.4 - 1994.3

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    Country: Japan

  3. Nagoya University   Faculty of Engineering

    1988.4 - 1992.3

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    Country: Japan

Professional Memberships 36

  1. 日本医用画像工学会

    2020

  2. 電子情報通信学会   医用画像研究会専門委員会幹事

    2007.4

  3. 日本医用画像工学会   幹事

    2009.4

  4. 日本生体医工学会   代議員

    2007.4 - 2010.3

  5. IEEE

  6. SPIE   SPIE Medical Imaging Program Committee

    2005.4

  7. 日本CT検診学会

    2020.4

  8. 東海支部連合大会

    2020.4

  9. 情報処理学会

    2020.4

  10. 日本がん検診・診断学会

    2020.4

  11. 日本呼吸内視鏡学会

    2020.4

  12. 日本生体医工学会

    2020.4

  13. 日本消化器内視鏡学会

    2020.4

  14. 日本VR医学会   評議員

    2009.4 - 2011.3

  15. 日本コンピュータ外科学会   理事

    2008.4

  16. 電子情報通信学会   医用画像研究会幹事

    2007.4

  17. MICCAI (Medical Image Computing and Computer Assisted Surgery   Program Committee

    2007.4

  18. SPIE Medical Imaging Conference 2007, Computer Aided Diagnosis   Program Committee

    2007.4 - 2009.3

  19. SPIE Medical Imaging Conference 2007, Image Processing   Program Committee

    2007.4 - 2009.3

  20. 電子情報通信学会   医療情報通信技術時限研究専門委員会専門委員

    2006.4 - 2008.3

  21. SPIE Medical Imaging Conference 2007, Image Processing   Program Committee

    2006.4 - 2008.3

  22. SPIE Medical Imaging Conference 2007, Computer Aided Diagnosis   Program Committee

    2006.4 - 2008.3

  23. コンピュータ支援画像診断学会   評議員

    2005.4

  24. International Journal of Computer Assisted Radiology and Surgery   Editorial Board

    2005.4

  25. Journal Medical Image Analysis   Editorial Board

    2005.4

  26. 電子情報通信学会   医用画像研究会幹事補佐

    2005.4 - 2008.3

  27. MICCAI (Medical Image Computing and Computer Assisted Intervention)   Area chair

    2005.4 - 2007.3

  28. SPIE Medical Imaging Conference 2006, Image Processing   Program Committee

    2005.4 - 2007.3

  29. MICCAI (Medical Image Computing and Computer Assisted Intervention)   Reviewer

    2004.4 - 2006.3

  30. 電子情報通信学会   医用画像研究会専門委員

    2003.4 - 2005.3

  31. 日本エム・イー学会   研究奨励賞選定委員会委員

    2003.4 - 2005.3

  32. MICCAI (Medical Image Computing and Computer Assisted Intervention)   Referee

    2003.4 - 2004.3

  33. Japan Society of Computer Assisted Syrgery

    2002.4

  34. CARS (Computer Assisted Radiology and Surgery)   Program Committee

    2001.4 - 2008.3

  35. Medical Image Analysis   Ad hoc Reviewer

  36. IEEE Transactions on Medical Imaging   Ad hoc Reviewer

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Committee Memberships 27

  1. 学内   TMI卓越大学院広報委員会委員  

    2020.12   

  2. 一般財団法人高度情報科学技術研究機構   HPCI連携サービス委員  

    2020.5 - 2021.3   

  3. 学内   東山キャンパス倫理審査委員  

    2020.4   

  4. 学内   情報連携推進本部業務会議 委員  

    2020.4   

  5. 学内   情報メディア教育システム運営協議会  

    2020.4   

  6. 学内   情報セキュリティ組織連絡協議会委員  

    2020.4   

  7. 学内   情報メディア教育システム専門委員  

    2020.4   

  8. 学内   プロジェクト・業務専門員会委員  

    2020.4   

  9. 学内   セキュリティ専門委員  

    2020.4   

  10. 学内   全国共同利用システム専門委員  

    2020.4   

  11. 学内   情報連携推進本部会議  

    2020.4   

  12. 学内   情報連携統括本部情報戦略室  

    2020.4   

  13. 学内   情報連携統括本部会議委員  

    2020.4   

  14. 学内   数理・データ科学教育研究センター 教育専門委員  

    2020.4   

  15. 学内   数理・データ科学教育研究センター運営委員  

    2020.4   

  16. 学内   全学技術センター運営専門委員会技術支援室委員  

    2020.4   

  17. 学内   全学技術センター運営委員会運営専門委員  

    2020.4   

  18. 学内   全学技術センター運営委員会人事委員  

    2020.4   

  19. 学内   連合第2群会議委員  

    2020.4   

  20. 学内   将来構想分科会委員  

    2020.4   

  21. 学内   教育分科会(全学教育委員会)委員  

    2020.4   

  22. 学内   安全保障委員  

    2020.4   

  23. 公益財団法人 テルモ生命科学振興財団   研究開発助成選考委員  

    2020.4 - 2022.3   

  24. 国立研究開発法人医薬基盤・健康・栄養研究所   国立研究開発法人医薬基盤・健康・栄養研究所SIP評価委員  

    2020.4 - 2022.3   

  25. 学内   CIBoG 運営委員  

    2019.4   

  26. 学内   CIBoGカリキュラム委員  

    2019.4   

  27. 一般社団法人 日本コンピュータ外科学会   国際委員会委員  

    2017.12 - 2019.9   

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Awards 21

  1. The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology

    2022.4   MEXT  

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

  2. 日本医用画像工学会論文賞

    2009.8   日本医用画像工学会  

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    Country:Japan

    計算機支援医用画像のための共通基盤システムの開発

  3. 功績賞

    2021.10   日本医用画像工学会  

  4. 文部科学大臣表彰 若手科学者賞

    2006.4   文部科学省  

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    Country:Japan

    仮想化内視鏡システム開発に対する貢献が評価されたものである。

  5. Certificate of Merit, Education Exhibit, Radiological Society of North America

    2009.11   RSNA (Radiological Society of North America)  

  6. 日本コンピュータ外科学会 2016年度講演論文賞

    2017.10   一般社団法人 日本コンピュータ外科学会  

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

  7. Fellow

    2015.10   MICCAI  

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    Country:Germany

  8. Magna Cum Laude Education Exhibit

    2014.12   Radiological Society of North America  

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    Country:United States

  9. Conference 8315, Honorable Mention Poster Award

    2012.2   SPIE Medical Imaging 2012: Computer-Aided Diagnosis  

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    Country:United States

  10. Honorable Mention Poster Award

    2011.2   SPIE Medical Imaging 2011: Image Processing  

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    Country:United States

  11. 2009年度 CAS Young Investigator Award ゴールド賞(日立メディコ賞)

    2010.11   第19回日本コンピュータ外科学会大会  

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    Country:Japan

  12. Honorable Mention Poster Award

    2010.2   SPIE Medical Imaging 2010: Computer-Aided Diagnosi  

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    Country:United States

  13. Certificate of Merit Education Exhibit

    2009.11   RSNA(Radiological Society of North America)  

  14. Certificate of Merit

    2004.11   Radiological Society of North America  

  15. International Society of Computer Assisted Surgery

    2004.6   Best Poster Award (1st Prize)  

  16. 電子情報通信学会ソサイエティ論文賞

    2000  

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    Country:Japan

  17. 日本気管支学会論文賞

    2000  

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    Country:Japan

  18. 丹羽記念賞

    1998  

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    Country:Japan

  19. 日本医用画像工学会奨励賞

    1997  

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    Country:Japan

  20. 日本エム・イー学会論文賞

    1997  

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    Country:Japan

  21. 日本医用画像工学会奨励賞

    1995  

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    Country:Japan

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Papers 1687

  1. Label cleaning and propagation for improved segmentation performance using fully convolutional networks Reviewed

    Takaaki Sugino, Yutaro Suzuki, Taichi Kin, Nobuhito Saito, Shinya Onogi, Toshihiro Kawase, Kensaku Mori, Yoshikazu Nakajima

    International Journal of Computer Assisted Radiology and Surgery     2021.3

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

    DOI: https://doi.org/10.1007/s11548-021-02312-5

  2. Predicting Violence Rating Based on Pairwise Comparison. Reviewed

    Ying JI, Yu WANG, Jien KATO, Kensaku MORI

    IEICE Transactions on Information and Systems   Vol. E103.D ( 12 ) page: 2578 - 2589   2020.12

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    Authorship:Last author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: https://doi.org/10.1587/transinf.2020EDP7056

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

    Ruiyun Zhu, Masahiro Oda, Yuichiro Hayashi, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara & Kensaku Mori   Vol. 18 ( 3 ) page: 461 - 472   2023.3

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

    DOI: 10.1007/s11548-022-02767-0

    Web of Science

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  4. Anatomy Aware-based 2.5D Bronchoscope Tracking for Image-guided Bronchoscopic Navigation Invited Reviewed

    Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Takayuki Kitasaka, Hayato Itto, Hirotoshi honma,Hirotsugu takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2022.12

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

    DOI: 10.1080/21681163.2022.2152728

    Web of Science

    Scopus

  5. Database-driven patient-specific registration error compensation method for image-guided laparoscopic surgery Invited Reviewed

    Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery     2022.12

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

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17 ( 11 ) page: 2051 - 2063   2022.10

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  7. Surgical Assistance in Laparoscopic Surgery Using AI Invited Reviewed

    HAYASHI Yuichiro, MORI Kensaku

    Medical Imaging Technology   Vol. 40 ( 4 ) page: 164 - 169   2022.9

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Society of Medical Imaging Technology  

    <p>Laparoscopic surgery is currently performed as one of surgical procedures for various organs. Laparoscopic surgery requires highly skill of surgeon. Therefore, computer aided surgery which is used computer technology for assisting surgery has been researched. These assistances are sometimes referred as surgical navigation. In recent year, as the development of AI (Artificial Intelligence) technology, there are many researches on laparoscopic video analysis using deep learning for assisting laparoscopic surgery. In this paper, we introduce our researches about laparoscopic video analysis using AI.</p>

    DOI: 10.11409/mit.40.164

    CiNii Research

  8. AI for VR Invited Reviewed

    森 健策

    日本VR医学会学術大会プログラム・抄録集   Vol. 2022 ( 0 ) page: 9 - 9   2022.8

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:日本VR医学会  

    DOI: 10.24764/jsmvr.2022.0_9

    CiNii Research

  9. 30年間の医用画像研究経験を振り返り未来を考える Invited Reviewed

    森 健策

    情報・システムソサイエティ誌   Vol. 27 ( 1 ) page: 16 - 17   2022.5

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:一般社団法人電子情報通信学会  

    DOI: 10.1587/ieiceissjournal.27.1_16

    CiNii Research

  10. Depth Estimation from Single-shot Monocular Endoscope Image Using Image Domain Adaptation And Edge-Aware Depth Estimation Reviewed

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

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization   Vol. 10 ( 3 ) page: 266 - 273   2022.5

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

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

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization   Vol. 10 ( 3 ) page: 289 - 298   2022.5

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

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

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization   Vol. 10 ( 3 ) page: 274 - 282   2022.5

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

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

    Journal of Medical Imaging   Vol. 9 ( 2 ) page: 024003-1 - 28   2022.4

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  14. Artificial Intelligence for Computer Vision in Surgery: A Call for Developing Reporting Guidelines. Invited Reviewed

    Kitaguchi D, Watanabe Y, Madani A, Hashimoto DA, Meireles OR, Takeshita N, Mori K, Ito M, Computer Vision in Surgery International Collaborative.

    Annals of surgery   Vol. 275 ( 4 ) page: e609 - e611   2022.4

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Annals of surgery  

    DOI: 10.1097/SLA.0000000000005319

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  15. Evaluation in real-time use of artificial intelligence during colonoscopy to predict relapse of ulcerative colitis: a prospective study Invited Reviewed

    Yasuharu Maeda, Shin-ei Kudo, Noriyuki Ogata, Masashi Misawa, Marietta Iacucci, Mayumi Homma, Tetsuo Nemoto, Kazumi Takishima, Kentaro Mochida, Hideyuki Miyachi, Toshiyuki Baba, Kensaku Mori, Kazuo Ohtsuka, Yuichi Mori

    Gastrointestinal Endoscopy     2022.4

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  16. Artificial Intelligence-Based Total Mesorectal Excision Plane Navigation in Laparoscopic Colorectal Surgery. Invited Reviewed

    Igaki T, Kitaguchi D, Kojima S, Hasegawa H, Takeshita N, Mori K, Kinugasa Y, Ito M

    Diseases of the colon and rectum     2022.2

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

    DOI: 10.1097/DCR.0000000000002393

    PubMed

  17. A cascaded fully convolutional network framework for dilated pancreatic duct segmentation Invited Reviewed

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

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

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/s11548-021-02530-x

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

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

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

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    Authorship:Lead author  

    DOI: 10.1016/j.gie.2021.07.022

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

    T. Hu, M. Oda, Y. Hayashi, Z. Lu, K. K. Kumamaru, T. Akashi, S. Aoki, K. Mori, ``Aorta-aware GAN for non-contrast to artery contrasted CT translation and its application to abdominal aortic aneurysm detection

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17 ( 1 ) page: 97 - 105   2022.1

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  20. Binary polyp-size classification based on deep-learned spatial information, Invited Reviewed

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( 10 ) page: 1817 - 1828   2021.10

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/s11548-021-02477-z

    DOI: 10.1007/s11548-021-02477-z

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  21. Depth-based branching level estimation for bronchoscopic navigation Invited Reviewed

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( 10 ) page: 1795 - 1804   2021.10

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

    DOI: 10.1007/s11548-021-02460-8

    DOI: 10.1007/s11548-021-02460-8

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

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

    TRANSLATIONAL GASTROENTEROLOGY AND HEPATOLOGY   Vol. 6   page: 64   2021.10

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Translational Gastroenterology and Hepatology  

    Computer-aided diagnosis (CAD) for colonoscopy with use of artificial intelligence (AI) is catching increased attention of endoscopists. CAD allows automated detection and pathological prediction, namely optical biopsy, of colorectal polyps during real-time endoscopy, which help endoscopists avoid missing and/or misdiagnosing colorectal lesions. With the increased number of publications in this field and emergence of the AI medical device that have already secured regulatory approval, CAD in colonoscopy is now being implemented into clinical practice. On the other side, drawbacks and weak points of CAD in colonoscopy have not been thoroughly discussed. In this review, we provide an overview of CAD for optical biopsy of colorectal lesions with a particular focus on its clinical applications and limitations.

    DOI: 10.21037/tgh.2019.12.14

    Web of Science

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  23. Deep learning system for automatic detection of bladder tumors in cystoscopic images Invited 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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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    Web of Science

  24. Development of Diagnosis Assistant AI for COVID-19 Patients Invited Reviewed

    ODA Masahiro, ZHENG Tong, HAYASHI Yuichiro, MORI Kensaku

    Medical Imaging Technology   Vol. 39 ( 1 ) page: 13 - 19   2021.1

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Society of Medical Imaging Technology  

    <p>We introduce AIs for diagnosis assistance of COVID-19 patients from CT volumes that were developed in Nagoya University. Novel coronavirus disease 2019(COVID-19)spreads over the world causing the large number of infected patients and deaths. Diagnosis assistance by AI is effective for diagnosing the large number of patients that are caused by infective diseases. We developed diagnosis assistant AIs for COVID-19 cases that evaluate the typical-ness of COVID-19 case based on image appearances from a CT volume. We developed three essential methods for the AIs including the lung region segmentation method, the clustering method of lung region, and the COVID-19 typical-ness evaluation method. To develop the AIs, we utilized huge number of medical images stored in the cloud platform of medical bigdata. We confirmed our AI has high performance for diagnosis assistance in the evaluations using CT volumes of real COVID-19 patients.</p>

    DOI: 10.11409/mit.39.13

    CiNii Research

  25. Automated Detection of Spinal Schwannomas Utilizing Deep Learning Based on Object Detection from MRI Invited Reviewed International coauthorship

    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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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1097/BRS.0000000000003749

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  26. Depth Estimation from Single-shot Monocular Endoscope Image Using Image Domain Adaptation And Edge-Aware Depth Estimation Invited Reviewed

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

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2021

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    DOI: 10.1080/21681163.2021.2012835

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  27. Context encoder guided self-supervised siamese depth estimation based on stereo laparoscopic images Invited Reviewed

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

    Proc. SPIE 11598, Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling   Vol. 11598   2021

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    DOI: 10.1117/12.2582348

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  28. Bronchial orifice segmentation on bronchoscopic video frames based on generative adversarial depth estimation Invited Reviewed

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

    Proc. SPIE 11598, Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling   Vol. 11598   page: 115980N-1 - 7   2021

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    DOI: 10.1117/12.2582341

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

    Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

    LNCS12969   Vol. 12969 LNCS   page: 88 - 97   2021

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

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  30. Attention-guided pancreatic duct segmentation from abdominal CT volumes Invited Reviewed

    Chen Shen, Holger Roth, Yuichiro Hayashi, Masahiro Oda, Takaaki Miyamoto, Gen Sato, Kensaku Mori

    LNCS12969   Vol. 12969 LNCS   page: 46 - 55   2021

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

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  31. CURRENT STATUS AND FUTURE PERSPECTIVE ON ARTIFICIAL INTELLIGENCE FOR LOWER ENDOSCOPY Invited 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

    GASTROENTEROLOGICAL ENDOSCOPY   Vol. 63 ( 7 ) page: 1402 - 1416   2021

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japan Gastroenterological Endoscopy Society  

    <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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  32. Clinical and Genetic Characteristics of 18 Patients from 13 Japanese Families with CRX-associated retinal disorder: Identification of Genotype-phenotype Association Invited Reviewed

    Fujinami-Yokokawa Y., Fujinami K., Kuniyoshi K., Hayashi T., Ueno S., Mizota A., Shinoda K., Arno G., Pontikos N., Yang L., Liu X., Sakuramoto H., Katagiri S., Mizobuchi K., Kominami T., Terasaki H., Nakamura N., Kameya S., Yoshitake K., Miyake Y., Kurihara T., Tsubota K., Miyata H., Iwata T., Tsunoda K., Nishimura T., Hayashizaki Y., Kondo M., Shimozawa N., Horiguchi M., Yamamoto S., Kuze M., Naoi N., Machida S., Shimada Y., Nakamura M., Fujikado T., Hotta Y., Takahashi M., Mochizuki K., Murakami A., Kondo H., Ishida S., Nakazawa M., Hatase T., Matsunaga T., Maeda A., Noda K., Tanikawa A., Yamamoto S., Yamamoto H., Araie M., Aihara M., Nakazawa T., Sekiryu T., Kashiwagi K., Kosaki K., Piero C., Fukuchi T., Hayashi A., Hosono K., Mori K., Tanaka K., Furuya K., Suzuki K., Kohata R., Yanagi Y., Minegishi Y., Iejima D., Suga A., Rossmiller B.P., Pan Y., Oshima T., Nakayama M., Teruyama Y., Yamamoto M., Minematsu N., Sanbe H., Mori D., Kijima Y., Mawatari G., Kurata K., Yamada N., Itoh M., Kawaji H., Murakawa Y.

    Scientific Reports   Vol. 10 ( 1 )   2020.12

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    Inherited retinal disorder (IRD) is a leading cause of blindness, and CRX is one of a number of genes reported to harbour autosomal dominant (AD) and recessive (AR) causative variants. Eighteen patients from 13 families with CRX-associated retinal disorder (CRX-RD) were identified from 730 Japanese families with IRD. Ophthalmological examinations and phenotype subgroup classification were performed. The median age of onset/latest examination was 45.0/62.5 years (range, 15–77/25–94). The median visual acuity in the right/left eye was 0.52/0.40 (range, −0.08–2.00/−0.18–1.70) logarithm of the minimum angle of resolution (LogMAR) units. There was one family with macular dystrophy, nine with cone-rod dystrophy (CORD), and three with retinitis pigmentosa. In silico analysis of CRX variants was conducted for genotype subgroup classification based on inheritance and the presence of truncating variants. Eight pathogenic CRX variants were identified, including three novel heterozygous variants (p.R43H, p.P145Lfs*42, and p.P197Afs*22). A trend of a genotype-phenotype association was revealed between the phenotype and genotype subgroups. A considerably high proportion of CRX-RD in ADCORD was determined in the Japanese cohort (39.1%), often showing the mild phenotype (CORD) with late-onset disease (sixth decade). Frequently found heterozygous missense variants located within the homeodomain underlie this mild phenotype. This large cohort study delineates the disease spectrum of CRX-RD in the Japanese population.

    DOI: 10.1038/s41598-020-65737-z

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  33. Clinical characteristics in patients with ossification of the posterior longitudinal ligament: A prospective multi-institutional cross-sectional study Invited Reviewed

    Hirai T., Yoshii T., Ushio S., Mori K., Maki S., Katsumi K., Nagoshi N., Takeuchi K., Furuya T., Watanabe K., Nishida N., Watanabe K., Kaito T., Kato S., Nagashima K., Koda M., Ito K., Imagama S., Matsuoka Y., Wada K., Kimura A., Ohba T., Katoh H., Matsuyama Y., Ozawa H., Haro H., Takeshita K., Watanabe M., Matsumoto M., Nakamura M., Yamazaki M., Okawa A., Kawaguchi Y.

    Scientific Reports   Vol. 10 ( 1 )   2020.12

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    Ossification of the posterior longitudinal ligament (OPLL) can occur throughout the entire spine and can sometimes lead to spinal disorder. Although patients with OPLL sometimes develop physical limitations because of pain, the characteristics of pain and effects on activities of daily living (ADL) have not been precisely evaluated in OPLL patients. Therefore, we conducted a multi-center prospective study to assess whether the symptoms of cervical OPLL are different from those of cervical spondylosis (CS). A total of 263 patients with a diagnosis of cervical OPLL and 50 patients with a diagnosis of CS were enrolled and provided self-reported outcomes, including responses to the Japanese Orthopaedic Association (JOA) Cervical Myelopathy Evaluation Questionnaire (JOACMEQ), JOA Back Pain Evaluation Questionnaire (JOABPEQ), visual analog scale (VAS), and SF-36 scores. The severity of myelopathy was significantly correlated with each domain of the JOACMEQ and JOABPEQ. There was a negative correlation between the VAS score for each domain and the JOA score. There were significantly positive correlations between the JOA score and the Mental Health, Bodily Pain, Physical Functioning, Role Emotional, and Role Physical domains of the SF-36. One-to-one matching resulted in 50 pairs of patients with OPLL and CS. Although there was no significant between-group difference in scores in any of the domains of the JOACMEQ or JOABPEQ, the VAS scores for pain or numbness in the buttocks or limbs were significantly higher in the CS group; however, there was no marked difference in low back pain, chest tightness, or numbness below the chest between the two study groups. The scores for the Role Physical and Body Pain domains of the SF-36 were significantly higher in the OPLL group than in the CS group, and the mean scores for the other domains was similar between the two groups. The results of this study revealed that patients with OPLL were likely to have neck and low back pain and restriction in ADL. No specific type of pain was found in patients with OPLL when compared with those who had CS.

    DOI: 10.1038/s41598-020-62278-3

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  34. Robust endocytoscopic image classificationbased on higher-order symmetric tensoranalysis and multi-scale topologicalstatistics 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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    DOI: 10.1007/s11548-020-02255-3

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

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

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2020.11

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    DOI: https://doi.org/10.1080/21681163.2020.1835560

  36. Clinical impact of Endoscopic Surgical Skill Qualification System (ESSQS) by Japan Society for Endoscopic Surgery (JSES) for laparoscopic distal gastrectomy and low anterior resection based on the National Clinical Database (NCD) registry. Invited Reviewed

    Akagi T, Endo H, Inomata M, Yamamoto H, Mori T, Kojima K, Kuroyanagi H, Sakai Y, Nakajima K, Shiroshita H, Etoh T, Saida Y, Yamamoto S, Hasegawa H, Ueno H, Kakeji Y, Miyata H, Kitagawa Y, Watanabe M

    Annals of gastroenterological surgery   Vol. 4 ( 6 ) page: 721 - 734   2020.11

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    DOI: 10.1002/ags3.12384

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  37. A visual SLAM-based bronchoscope tracking scheme for bronchoscopic navigation Invited 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   2020.10

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    DOI: 10.1007/s11548-020-02241-9

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  38. Station number assignment to abdominal lymph node for assisting gastric cancer surgery Reviewed

    Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2020.10

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    DOI: https://doi.org/10.1080/21681163.2020.1835543

  39. A deformable model for navigated laparoscopic gastrectomy based on finite elemental method Invited 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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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Minimally Invasive Therapy and Allied Technologies  

    Background: Accurate registration for surgical navigation of laparoscopic surgery is highly challenging due to vessel deformation. Here, we describe the design of a deformable model with improved matching accuracy by applying the finite element method (FEM). Material and methods: ANSYS software was used to simulate an FEM model of the vessel after pull-up based on laparoscopic gastrectomy requirements. The central line of the FEM model and the central line of the ground truth were drawn and compared. Based on the material and parameters determined from the animal experiment, a perigastric vessel FEM model of a gastric cancer patient was created, and its accuracy in a laparoscopic gastrectomy surgical scene was evaluated. Results: In the animal experiment, the FEM model created with Ogden foam material exhibited better results. The average distance between the two central lines was 6.5mm, and the average distance between their closest points was 3.8 mm. In the laparoscopic gastrectomy surgical scene, the FEM model and the true artery deformation demonstrated good coincidence. Conclusion: In this study, a deformable vessel model based on FEM was constructed using preoperative CT images to improve matching accuracy and to supply a reference for further research on deformation matching to facilitate laparoscopic gastrectomy navigation.

    DOI: 10.1080/13645706.2019.1625926

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  40. Automated laparoscopic colorectal surgery workflow recognition using artificial intelligence: Experimental research Invited Reviewed

    Kitaguchi Daichi, Takeshita Nobuyoshi, Matsuzaki Hiroki, Oda Tatsuya, Watanabe Masahiko, Mori Kensaku, Kobayashi Etsuko, Ito Masaaki

    INTERNATIONAL JOURNAL OF SURGERY   Vol. 79   page: 88 - 94   2020.7

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    Background: Identifying laparoscopic surgical videos using artificial intelligence (AI) facilitates the automation of several currently time-consuming manual processes, including video analysis, indexing, and video-based skill assessment. This study aimed to construct a large annotated dataset comprising laparoscopic colorectal surgery (LCRS) videos from multiple institutions and evaluate the accuracy of automatic recognition for surgical phase, action, and tool by combining this dataset with AI. Materials and methods: A total of 300 intraoperative videos were collected from 19 high-volume centers. A series of surgical workflows were classified into 9 phases and 3 actions, and the area of 5 tools were assigned by painting. More than 82 million frames were annotated for a phase and action classification task, and 4000 frames were annotated for a tool segmentation task. Of these frames, 80% were used for the training dataset and 20% for the test dataset. A convolutional neural network (CNN) was used to analyze the videos. Intersection over union (IoU) was used as the evaluation metric for tool recognition. Results: The overall accuracies for the automatic surgical phase and action classification task were 81.0% and 83.2%, respectively. The mean IoU for the automatic tool segmentation task for 5 tools was 51.2%. Conclusions: A large annotated dataset of LCRS videos was constructed, and the phase, action, and tool were recognized with high accuracy using AI. Our dataset has potential uses in medical applications such as automatic video indexing and surgical skill assessments. Open research will assist in improving CNN models by making our dataset available in the field of computer vision.

    DOI: 10.1016/j.ijsu.2020.05.015

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  41. Clinical application of a surgical navigation system based on virtual thoracoscopy for lung cancer patients: real time visualization of area of lung cancer before induction therapy and optimal resection line for obtaining a safe surgical margin during surgery Invited Reviewed

    Nakamura Shota, Hayashi Yuichiro, Kawaguchi Koji, Fukui Takayuki, Hakiri Shuhei, Ozeki Naoki, Mori Shunsuke, Goto Masaki, Mori Kensaku, Yokoi Kohei

    JOURNAL OF THORACIC DISEASE   Vol. 12 ( 3 ) page: 672 - 679   2020.3

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    Background: We have developed a surgical navigation system that presents virtual thoracoscopic images using computed tomography (CT) image data, as if you are observing intra-thoracic cavity in synchronization with the real thoracoscopic view. Using this system, we made it possible to simultaneously visualize the ‘area of lung cancer before induction therapy’ and the ‘optimal resection line for obtaining a safe surgical margin’ as a virtual thoracoscopic view. We applied this navigation system in the clinical setting in operations for lung cancer patients with chest wall invasion after induction chemoradiotherapy. Methods: The proposed surgical navigation system consisted of a three-dimensional (3D) positional tracker and a virtual thoracoscopy system. The 3D positional tracker was used to recognize the positional information of the real thoracoscope. The virtual thoracoscopy system generated virtual thoracoscopic views based on CT image data. Combined with these two technologies, patient-to-image registration was performed in two patients, and the results generated a virtual thoracoscopic view that was synchronized with the real thoracoscopic view. Results: The operations were started with video-assisted thoracic surgery (VATS), and the navigation system was activated at the same time. The virtual thoracoscopic view was synchronized with the real thoracoscopic view, which also simultaneously indicated the ‘area of lung cancer before induction therapy’ and the ‘optimal resection lines for obtaining a safe surgical margin’. We marked the optimal lines using an electric scalpel, and then performed lobectomy and chest wall resection with a sufficient surgical margin using these landmarks. Pathological examinations confirmed that the surgical margin was negative. No complications related to the navigation system were encountered during or after the procedures. Conclusions: Using this proposed navigation system, we could obtain a ‘CT-derived virtual intrathoracic 3D view of the patient’ that was aligned with the thoracoscopic view during surgery. The accurate identification of areas of cancer invasion before induction therapy using this system might be a useful for determining optimal surgical resection lines.

    DOI: 10.21037/jtd.2019.12.108

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

    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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    DOI: 10.1016/j.media.2019.101623

  43. [Pharmacological action and clinical effect of tedizolid phosphate (SIVEXTRO<sup>®</sup> Tablets 200 mg, for iv infusion 200 mg), a novel oxazolidinone-class antibacterial drug]. Invited Reviewed

    Mori M, Takase A

    Nihon yakurigaku zasshi. Folia pharmacologica Japonica   Vol. 155 ( 5 ) page: 332 - 339   2020

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    DOI: 10.1254/fpj.20013

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  44. 3Dプリンティングの最新動向 Invited

    森 健策

    インナービジョン   Vol. 35   page: 36 - 37   2020

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

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

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

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    This paper presents an automated classification method of infective and non-infective diseases from anterior eye images. Treatments for cases of infective and non-infective diseases are different. Distinguishing them from anterior eye images is important to decide a treatment plan. Ophthalmologists distinguish them empirically. Quantitative classification of them based on computer assistance is necessary. We propose an automated classification method of anterior eye images into cases of infective or non-infective disease. Anterior eye images have large variations of the eye position and brightness of illumination. This makes the classification difficult. If we focus on the cornea, positions of opacified areas in the corneas are different between cases of the infective and non-infective diseases. Therefore, we solve the anterior eye image classification task by using an object detection approach targeting the cornea. This approach can be said as "anatomical structure focused image classification". We use the YOLOv3 object detection method to detect corneas of infective disease and corneas of non-infective disease. The detection result is used to define a classification result of an image. In our experiments using anterior eye images, 88.3% of images were correctly classified by the proposed method.

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  46. Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning Invited Reviewed

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

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Vol. 12444 LNCS   page: 192 - 200   2020

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    The performance of deep learning based methods strongly relies on the number of datasets used for training. Many efforts have been made to increase the data in the medical image analysis field. However, unlike photography images, it is hard to generate centralized databases to collect medical images because of numerous technical, legal, and privacy issues. In this work, we study the use of federated learning between two institutions in a real-world setting to collaboratively train a model without sharing the raw data across national boundaries. We quantitatively compare the segmentation models obtained with federated learning and local training alone. Our experimental results show that federated learning models have higher generalizability than standalone training.

    DOI: 10.1007/978-3-030-60548-3_19

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  47. Abdominal artery segmentation method from CT volumes using fully convolutional neural network Invited 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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  48. A view of three dimensional unit structures of alveoli in peripheral lung Invited 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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  49. ARTIFICIAL INTELLIGENCE-ASSISTED POLYP DETECTION SYSTEM FOR COLONOSCOPY, BASED ON THE LARGEST AVAILABLE COLLECTION OF CLINICAL VIDEO DATA FOR MACHINE LEARNING Invited 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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  50. Development of a new laparoscopic detection system for gastric cancer using near-infrared light-emitting clips with glass phosphor Invited Reviewed

    Inada S., Nakanishi H., Oda M., Mori K., Ito A., Hasegawa J., Misawa K., Fuchi S.

    Micromachines   Vol. 10 ( 2 )   2019.1

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    Laparoscopic surgery is now a standard treatment for gastric cancer. Currently, the location of the gastric cancer is identified during laparoscopic surgery via the preoperative endoscopic injection of charcoal ink around the primary tumor; however, the wide spread of injected charcoal ink can make it difficult to accurately visualize the specific site of the tumor. To precisely identify the locations of gastric tumors, we developed a fluorescent detection system comprising clips with glass phosphor (Yb 3+ , Nd 3+ doped to Bi 2 O 3 -B 2 O 3 -based glasses, size: 2 mm × 1 mm × 3 mm) fixed in the stomach and a laparoscopic fluorescent detection system for clip-derived near-infrared (NIR) light (976 nm). We conducted two ex vivo experiments to evaluate the performance of this fluorescent detection system in an extirpated pig stomach and a freshly resected human stomach and were able to successfully detect NIR fluorescence emitted from the clip in the stomach through the stomach wall by the irradiation of excitation light (λ: 808 nm). These results suggest that the proposed combined NIR light-emitting clip and laparoscopic fluorescent detection system could be very useful in clinical practice for accurately identifying the location of a primary gastric tumor during laparoscopic surgery.

    DOI: 10.3390/mi10020081

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  51. Automated Hand Eye Calibration in Laparoscope Holding Robot for Robot Assisted Surgery Invited 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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  52. Colonoscope tracking method based on shape estimation network Invited Reviewed

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

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

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    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 confirmed that tracking errors of the proposed method was enough small to perform navigation in the ascending, transverse, and descending colons.

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

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

    Proc. SPIE 10578, Medical Imaging 2018   Vol. 10578   page: 105780V-1-105780V-6   2018

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    DOI: 10.1117/12.2293431

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  54. Cascade classification of lesions for automated pathological diagnosis Invited Reviewed

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

    Proc. SPIE 10575, Medical Imaging 2018   Vol. 10575   page: 1057516-1-1057516-6   2018

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    DOI: 10.1117/12.2293495

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  55. 3Dプリンタの最新動向 Invited

    森 健策

    インナービジョン   Vol. 33   page: 35 - 36   2018

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    CiNii Research

  56. BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images Invited 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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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

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

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  57. Colon Shape Estimation Method for Colonoscope Tracking Using Recurrent Neural Networks Invited Reviewed

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

    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT IV   Vol. 11073   page: 176 - 184   2018

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/978-3-030-00937-3_21

    Web of Science

  58. Deep Learning and Its Application to Medical Image Segmentation Invited Reviewed

    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

    CiNii Research

  59. Develop and Validate a Finite Element Method Model for Deformation Matching of Laparoscopic Gastrectomy Navigation Invited 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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  60. Airway Segmentation from 3D Chest CT Volumes Based on Volume of Interest Using Gradient Vector Flow Invited Reviewed

    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

    CiNii Research

  61. <b>3Dプリンターの基礎と医療応用</b> Invited Reviewed

    森 健策

    心臓   Vol. 49 ( 11 ) page: 1104 - 1113   2017.11

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:公益財団法人 日本心臓財団  

    DOI: 10.11281/shinzo.49.1104

    CiNii Research

  62. Automated mediastinal lymph node detection from CT volumes based on intensity targeted radial structure tensor analysis Invited

    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 ( 04 ) page: 1   2017.11

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    DOI: 10.1117/1.jmi.4.4.044502

    CiNii Research

  63. Automatic anatomical labeling of arteries and veins using conditional random fields Invited Reviewed

    akayuki 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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  64. Artificial Intelligence for Endocytoscopy Provides Fully Automated Diagnosis of Histological Remission in Ulcerativ E. Coli Tis Invited 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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  65. Computer-Aided Diagnosis Based on Endocytoscopy With Narrow-Band Imaging Allows Accurate Diagnosis of Diminutive Colorectal Lesions Invited 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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  66. Can Artificial Intelligence Correctly Diagnose Sessile Serrated Adenomas/Polyps? Invited 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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  67. Diagnostic Ability of Automated Diagnosis System Using Endocytoscopy for Invasive Colorectal Cancer Invited 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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  68. Influence of using 3D images and 3D-printed objects on the formation of spatial mental models of experts and novices Invited Reviewed

    MAEHIGASHI Akihiro, MIWA Kazuhisa, ODA Masahiro, NAKAMURA Yoshihiko, MORI Kensaku, IGAMI Tsuyoshi

    JSAI Technical Report, SIG-ALST   Vol. 79 ( 0 ) page: 08   2017.3

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Society for Artificial Intelligence  

    DOI: 10.11517/jsaialst.79.0_08

    CiNii Research

  69. Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume Invited Reviewed

    Qier Meng, Takayuki Kitasaka, Yukitaka Nimura, Masahiro Oda, Junji Ueno, Kensaku Mori

    International Journal of Computer Assisted Radiology Surgery   Vol. 12 ( 2 ) page: 245 - 261   2017.2

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    DOI: 10.1007/s11548-016-1492-2

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  70. 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation Invited Reviewed

    Oda Masahiro, Shimizu Natsuki, Roth Holger R., Karasawa Ken'ichi, Kitasaka Takayuki, Misawa Kazunari, Fujiwara Michitaka, Rueckert Daniel, Mori Kensaku

    DEEP LEARNING IN MEDICAL IMAGE ANALYSIS AND MULTIMODAL LEARNING FOR CLINICAL DECISION SUPPORT   Vol. 10553   page: 222 - 230   2017

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    This paper presents a fully automated atlas-based pancreas segmentation method from CT volumes utilizing 3D fully convolutional network (FCN) feature-based pancreas localization. Segmentation of the pancreas is difficult because it has larger inter-patient spatial variations than other organs. Previous pancreas segmentation methods failed to deal with such variations. We propose a fully automated pancreas segmentation method that contains novel localization and segmentation. Since the pancreas neighbors many other organs, its position and size are strongly related to the positions of the surrounding organs. We estimate the position and the size of the pancreas (localization) from global features by regression forests. As global features, we use intensity differences and 3D FCN deep learned features, which include automatically extracted essential features for segmentation. We chose 3D FCN features from a trained 3D U-Net, which is trained to perform multi-organ segmentation. The global features include both the pancreas and surrounding organ information. After localization, a patient-specific probabilistic atlas-based pancreas segmentation is performed. In evaluation results with 146 CT volumes, we achieved 60.6% of the Jaccard index and 73.9% of the Dice overlap.

    DOI: 10.1007/978-3-319-67558-9_26

    Web of Science

    Scopus

  71. 3Dプリンタ・ユーザーインターフェイス等の最新動向 Invited

    森 健策

    インナービジョン   Vol. 32   page: 44 - 45   2017

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    CiNii Research

  72. 3D Printing for Medical Application Invited

    MORI Kensaku

    Medical Imaging and Information Sciences   Vol. 34 ( 1 ) page: 1 - 6   2017

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    <p>This paper briefly introduces 3D printing technology for medical applications. 3D printing technology is obtaining a lot of attentions from various fields including rapid prototyping and manufacturing, home use and medical applications. Medical applications of 3D printing are including:(a)diagnostic aid,(b)surgical aid,(c)medical education,(d)medical training, and(e)re-generative medicine. In this short summary, we will briefly explain the various mechanism of 3D printing and several printing techniques for reproducing organ models by 3D printing techniques. Also the recent topics in international conferences are introduced here.</p>

    DOI: 10.11318/mii.34.1

    CiNii Research

  73. 3Dプリンタの医療応用 Invited

    森 健策

    医用画像情報学会雑誌   Vol. 34   page: 1 - 6   2017

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    CiNii Research

  74. 3Dプリンタ-の基礎と医療応用 Invited

    森 健策

    月刊心臓   Vol. 49   page: 1104 - 1113   2017

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    CiNii Research

  75. Automatic Segmentation of Head Anatomical Structures from Sparsely-annotated Images Invited 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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    Web of Science

  76. Computer-Aided Diagnosis of Mammographic Masses Using Geometric Verification-Based Image Retrieval Invited Reviewed

    Li Qingliang, Shi Weili, Yang Huamin, Zhang Huimao, Li Guoxin, Chen Tao, Mori Kensaku, Jiang Zhengang

    MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS   Vol. 10134   2017

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/12.2255799

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  77. Comparison of the Deep-Learning-Based Automated Segmentation Methods for the Head Sectioned Images of the Virtual Korean Human Project Invited 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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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

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  78. A study on improvement of airway segmentation using Hybrid method Invited Reviewed

    Qier M., Kitasaka T., Nimura Y., Oda M., Mori K.

    Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015     page: 549 - 553   2016.6

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    This paper presents a method for extracting an airway region from 3D chest CT volumes that uses a combination of tube enhancement filters, voxel classification based on machine learning methods and graph-cut algorithm. Lots of previous methods utilize region growing or level set algorithms without any prior knowledge of bronchi, which always fail when they reach to the peripheral bronchi. In this paper, a method of extraction based on airway shape and machine learning is proposed. The proposed method detects candidate voxels of bronchial regions by using two types of enhancement filters, and a classifier model is built for selecting the proper candidates regions based on intensity and shape features and finally the selected candidate voxels are connected by graph-cut algorithm. We applied this method on six cases of 3D chest CT volumes. The results show that this method can extract the smaller airway branches without leaking into the lung parenchyma areas.

    DOI: 10.1109/ACPR.2015.7486563

    Scopus

  79. Characterization of Colorectal Lesions Using a Computer-Aided Diagnostic System for Narrow-Band Imaging Endocytoscopy Invited Reviewed

    Misawa Masashi, Kudo Shin-ei, Mori Yuichi, Nakamura Hiroki, Kataoka Shinichi, Maeda Yasuharu, Kudo Toyoki, Hayashi Takemasa, Wakamura Kunihiko, Miyachi Hideyuki, Katagiri Atsushi, Baba Toshiyuki, Ishida Fumio, Inoue Haruhiro, Nimura Yukitaka, Mori Kensaku

    GASTROENTEROLOGY   Vol. 150 ( 7 ) page: 1531 - +   2016.6

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    DOI: 10.1053/j.gastro.2016.04.004

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  80. Clinical application of a surgical navigation system based on virtual laparoscopy in laparoscopic gastrectomy for gastric cancer Invited Reviewed

    Hayashi Yuichiro, Misawa Kazunari, Oda Masahiro, Hawkes David J., Mori Kensaku

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 11 ( 5 ) page: 827 - 836   2016.5

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/s11548-015-1293-z

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  81. Influences of 3D images and 3D-printed objects on mental model construction of liver structure Invited Reviewed

    MAEHIGASHI Akihiro, MIWA Kazuhisa, ODA Masahiro, NAKAMURA Yoshihiko, MORI Kensaku, IGAMI Tsuyoshi

    JSAI Technical Report, SIG-ALST   Vol. 76 ( 0 ) page: 14   2016.3

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Society for Artificial Intelligence  

    <p>In this study, we experimentally investigated the influence of a three-dimensional (3D) graphic image and a 3D-printed object on a spatial reasoning task in a situation where liver resection surgery was presupposed. The results of the study indicated that using a 3D-printed object produced more accurate and faster mental model construction of a liver structure than a 3D image. Using a 3D-printed object was assumed to reduce cognitive load and information accessing cost more than using a 3D image.</p>

    DOI: 10.11517/jsaialst.76.0_14

    CiNii Research

  82. 3Dプリンタ・ユーザーインターフェイス等の最新動向 Invited

    森 健策

    インナービジョン   Vol. -   page: 44 - 45   2016

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    CiNii Research

  83. 3Dプリンティングのハンドリングのノウハウ Invited

    森 健策

    インナービジョン   Vol. 31   page: 20 - 24   2016

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    CiNii Research

  84. Automated anatomical labeling of abdominal arteries and hepatic portal system extracted from abdominal CT volumes Invited Reviewed

    Matsuzaki Tetsuro, Oda Masahiro, Kitasaka Takayuki, Hayashi Yuichiro, Misawa Kazunari, Mori Kensaku

    MEDICAL IMAGE ANALYSIS   Vol. 20 ( 1 ) page: 152 - 161   2015.2

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    DOI: 10.1016/j.media.2014.11.002

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  85. Automated torso organ segmentation from 3D CT images using conditional random field Invited Reviewed

    Yukitaka Nimura, Yuichiro Hayashi, Takayuki Kitasaka, Kazunari Misawa, and Kensaku Mori

    Proceedings of SPIE Medical Imaging 2016   Vol. 9785   2015

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/12.2214845

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  86. 3Dプリンティングの現状と将来展望:医用画像処理と3Dプリンタによる臓器実体モデル作成とその利用 Invited

    森 健策

    光技術コンタクト   Vol. 53   page: 20 - 27   2015

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    CiNii Research

  87. A study on improvement of airway segmentation using Hybrid method Invited Reviewed

    Qier Meng, Kitasaka Takayuki, Nimura Yukitaka, Oda Masahiro, Mori Kensaku

    PROCEEDINGS 3RD IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION ACPR 2015     page: 549 - 553   2015

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    Web of Science

  88. Connection method of separated luminal regions of intestine from CT volumes Invited Reviewed

    Oda Masahiro, Kitasaka Takayuki, Furukawa Kazuhiro, Watanabe Osamu, Ando Takafumi, Hirooka Yoshiki, Goto Hidemi, Mori Kensaku

    MEDICAL IMAGING 2015: COMPUTER-AIDED DIAGNOSIS   Vol. 9414   2015

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/12.2081977

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  89. Automated Torso Organ Segmentation from 3D CT Images using Structured Perceptron and Dual Decompostion Invited Reviewed

    Nimura Yukitaka, Hayashi Yuichiro, Kitasaka Takayuki, Mori Kensaku

    MEDICAL IMAGING 2015: COMPUTER-AIDED DIAGNOSIS   Vol. 9414   2015

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/12.2081774

    Web of Science

  90. Automated branching pattern report generation for laparoscopic surgery assistance Invited Reviewed

    Oda Masahiro, Matsuzaki Tetsuro, Hayashi Yuichiro, Kitasaka Takayuki, Misawa Kazunari, Mori Kensaku

    MEDICAL IMAGING 2015: COMPUTER-AIDED DIAGNOSIS   Vol. 9414   2015

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/12.2082488

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  91. Development and clinical application of surgical navigation system for laparoscopic hepatectomy Invited Reviewed

    Hayashi Yuichiro, Igami Tsuyoshi, Hirose Tomoaki, Nagino Masato, Mori Kensaku

    MEDICAL IMAGING 2015: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING   Vol. 9415   2015

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1117/12.2082690

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  92. Development of a new detection device using a glass clip emitting infrared fluorescence for laparoscopic surgery of gastric cancer Invited Reviewed

    Inada Shunko Albano, Fuchi Shingo, Mori Kensaku, Hasegawa Junichi, Misawa Kazunari, Nakanishi Hayao

    6TH INTERNATIONAL CONFERENCE ON OPTICAL, OPTOELECTRONIC AND PHOTONIC MATERIALS AND APPLICATIONS (ICOOPMA) 2014   Vol. 619   2015

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    Authorship:Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.1088/1742-6596/619/1/012033

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

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 18   page: 473 - 482   2023.3

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  94. CT像からの腸閉塞検出における中心線を用いた後処理手法

    陳 思睿, 小田 紘久, 安 芹, 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

    電子情報通信学会技術研究報告(MI)信学技報   Vol. 122 ( 417 ) page: 223 - 228   2023.3

  95. 医用画像とAI Reviewed

    カレントテラピー   Vol. 41 ( 39 ) page: 79 - 79   2023.3

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  96. 術前画像情報を用いた腹腔鏡映像からの血管位置予測の検討

    榎本 圭吾, 林 雄一郎, 北坂 孝幸, 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) 信学技報   Vol. 122 ( 417 ) page: 63 - 68   2023.3

  97. グラフニューラルネットワークを用いた血管名自動命名における臓器特徴の有効性の調査

    出口 智也, 林 雄一郎, 北坂 孝幸, 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), 信学技報   Vol. 122 ( 417 ) page: 105 - 110   2023.3

  98. Average Templateを使ったCT像からのCOVID-19異常陰影領域セグメンテーション手法

    柳 凱, 小田 昌宏, 鄭 通, 林 雄一郎, 大竹 義人, 橋本 正弘, 明石 敏昭, 青木 茂樹, 森 健策

    電子情報通信学会技術研究報告(MI) 信学技報   Vol. 122 ( 47 ) page: 40 - 45   2023.3

  99. Comparative study of the Small Intestine segmentation based on 2D and 3D U-Nets

    Qin An, Hirohisa Oda, Sirui Chen, Yuichiro Hayashi, Takayuki Kitasaka, Hiroo Uchida, Akinari Hinoki, Kojiro Suzuki, Aitaro Takimoto, Masahiro Oda, Kensaku Mori

      Vol. 122 ( 417 ) page: 46 - 51   2023.3

  100. L-former : a lightweight transformer for realistic medical image generation and its application to super-resolution Reviewed

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

    proc. SPIE     2023.2

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

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

    Proc.SPIE12464     2023.2

  102. `Thrombosis region extraction and quantitative analysis in confocal laser scanning microscopic image sequence in in-vivo imaging Invited Reviewed

    Yunheng Wu, Masahiro Oda,Yuichiro Hayashi, Shuntaro Kawamura, Takanori Takebe, Kensaku Mori

    Proc.SPIE     2023.2

  103. Real bronchoscopic images-based bronchial nomenclature: a preliminary study Invited Reviewed

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

    Proc.SPIE     2023.2

  104. Improved method for COVID-19 classification of complex-architecture CNN from chest CT volumes using orthogonal ensemble networks Invited Reviewed

    Ryo Toda, Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

    Proc.SPIE     2023.2

  105. Octree cube constraints in PBD method for high resolution surgical simulation Reviewed

    Rintaro Miyazaki, Yuichiro Hayashi, Masahiro Oda, Kensaku Mori

    Proc.SPIE     2023.2

  106. Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-mixer Invited Reviewed

    Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

    Proc.SPIE     2023.2

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

    Leo Uramoto, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

    Proc.SPIE     2023.2

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

    Sadayuki Ito, Hiroaki Nakashima, Toshitaka Yoshii, Satoru Egawa, Kenichiro Sakai, Kazuo Kusano, Shinji Tsutui, Takashi Hirai, Yu Matsukura, Kanichiro Wada, Keiichi Katsumi, Masao Koda, Atsushi Kimura, Takeo Furuya, Satoshi Maki, Narihito Nagoshi, Norihiro Nishida, Yukitaka Nagamoto, Yasushi Oshima, Kei Ando, Masahiko Takahata, Kanji Mori, Hideaki Nakajima, Kazuma Murata, Masayuki Miyagi, Takashi Kaito, Kei Yamada, Tomohiro Banno, Satoshi Kato, Tetsuro Ohba, Satoshi Inami, Shunsuke Fujibayashi, Hiroyuki Katoh, Haruo Kanno, Masahiro Oda, Kensaku Mori, Hiroshi Taneichi, Yoshiharu Kawaguchi, Katsushi Takeshita, Morio Matsumoto, Masashi Yamazaki, Atsushi Okawa, Shiro Imagama

    Europian Spine Journal     2023.2

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  109. Surgical area recognition from laparoscopic images in laparoscopic gastrectomy for gastric cancer using label smoothing and uncertainty Invited Reviewed

    Yuichiro Hayashi,Kazunari Misawa, Kensaku Mori

    Proc. SPIE 12466     2023.2

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

    Kai Jiang, Masahiro Oda, Yuichiro Hayashi, Hironari Shiwaku, Masashi Misawa, Kensaku Mori

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization   Vol. 11 ( 4 ) page: 1271 - 1280   2023.2

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  111. KST-Mixer: Kinematic Spatio-Temporal Data Mixer For Colon Shape Estimation Reviewed

    Masahiro Oda, Kazuhiro Furukawa, Nassir Navab, Kensaku Mori

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2023.1

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  112. 人工知能(AI)の最新動向 RSNA2022におけるAI関連セッション Reviewed

    インナービジョン   Vol. 38 ( 2 ) page: 33 - 34   2023.1

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  113. Boundary-aware Feature and Prediction Refinement for Polyp Segmentation Reviewed

    ie Qiu, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kensaku Mori, ``Boundary-aware Feature and Prediction Refinement for Polyp Segmentation

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization     2022.12

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

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

    LNCS13594     2022.10

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  115. Joint multi organ and tumor segmentation from partial labels using federated learning Reviewed

    Chen Shen, Pochuan Wang, Dong Yang, Daguang Xu, Masahiro Oda, Po-Ting Chen, Kao-Lang Liu, Wei-Chin Liao, Chiou-Shann Fuh, Kensaku Mori , Weichung Wang, Holger R. Roth

    ,LNCS 13573     2022.10

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

    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

    LNCS13437     page: 736 - 744   2022.9

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

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

    LNCS13434     page: 467 - 477   2022.9

  118. GNN による血管名自動命名手法における臓器特徴の利用に関する検討 Invited Reviewed

    出口 智也, 林 雄一郎, 北坂 孝幸, 小田 昌宏, 三澤 一成, 森 健策

     第41回日本医用画像工学会大会予稿集     2022.7

  119. Confocal Laser Scanning Microscope Image Super Resolution for Biomedical Research Based on Two-Stage Generative Adversarial Network Invited Reviewed

    Yunheng WU, Masahiro ODA, Yuichiro HAYASHI, Takanori TAKEBE, Shogo NAGATA, Shuntaro KAWAMURA, Kensaku MORI

        page: 138 - 139   2022.7

  120. Co-Training for Semi-Supervised CT Segmentation of COVID-19 Invited Reviewed

    Kai LIU, Masahiro ODA, Tong ZHENG, Yuichiro HAYASHI, Yoshito OTAKE, Masahiro HASHIMOTO, Toshiaki AKASHI, Shigeki AOKI, Kensaku MORI

        page: 114 - 115   2022.7

  121. A Novel Centroid-attention based Hybrid Model for Subarachnoid Hemorrhage Classification on Imbalanced Data Invited Reviewed

    Zhongyang LU, Masahiro ODA,1, Yuichiro HAYASHI, Tao Hu, Hayato ITOH, Takeyuki WATADANI, Osamu ABE,Kensaku MORI

        page: 104 - 105   2022.7

  122. 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 Invited Reviewed

    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

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

  123. 境界情報を考慮する損失関数を用いたFCN による腹部 CT 像からの臓器領域抽出に関する研究 Invited Reviewed

    大野 真奈, 申 忱, Holger R. Roth, 小田 昌宏, 林 雄一郎, 三澤 一成, 森 健策

    第41回日本医用画像工学会大会予稿集     page: 106 - 107   2022.7

  124. 腹腔鏡映像からの血管領域自動抽出におけるDilated U‒Netの段数が 抽出精度に与える影響 Invited Reviewed

    榎本 圭吾 ,林 雄一郎,北坂 孝幸,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31回日本コンピュータ外科学会大会特集号   Vol. 24 ( 2 ) page: 22(5)-3   2022.6

  125. 腹腔鏡下胃切除術支援のための腹腔鏡映像からの膵臓領域抽出の検討 Invited Reviewed

    林 雄一郎, 辻 真治, 丘 杰, 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31回日本コンピュータ外科学会大会特集号   Vol. 24 ( 2 ) page: 22(5)-4   2022.6

  126. nnU‒Netによる肺マイクロCT像からの小葉間隔壁抽出 Invited Reviewed

    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 第31回日本コンピュータ外科学会大会特集号   Vol. 24 ( 2 ) page: 22(5)-6   2022.6

  127. コンピュータ外科におけるAIとVisionのドッキング―知能と知覚の結合による新たなコンピュータ外科 Invited Reviewed

    森 健策

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 24 ( 2 )   2022.6

  128. 大腸外科領域における情報支援内視鏡外科手術システムの開発 Invited Reviewed

    ]長谷川 寛, 北口 大地, 小島 成浩, 竹下 修由, 森 健策, 伊藤 雅昭

    日本コンピュータ外科学会誌 第31回日本コンピュータ外科学会大会特集号   Vol. 24 ( 2 )   2022.6

  129. Laparoscopic image classification based on surgical areas in laparoscopic gastrectomy, Invited Reviewed

    Y. Hayashi, K. Misawa, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17   page: s57 - 58   2022.6

  130. 3D bronchus anatomical structure measurement on real bronchoscopic images based on depth images estimated by deep neural network Reviewed

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17   page: s48 - s49   2022.6

  131. Extraction of respiratory bronchioles and alveolar ducts from micro-CT volumes with distance-based tubular structure filter Invited Reviewed

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17   page: s117 - s118   2022.6

  132. 2D+3D registration in deformation-adaptive super-resolution for medical images Invited Reviewed

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17   page: s105 - s106   2022.6

  133. Automatic Detection of Bladder Tumors in Narrow-Band Imaging Cystoscopic Images by tiny-YOLO Invited Reviewed

    J. Mutaguchi, M. Oda, E. Kashiwagi, J. Inokuchi, K. Mori, M. Eto

    International Journal of Computer Assisted Radiology and Surgery   Vol. 17   page: s86 - s86   2022.6

  134. 30年間の医用画像研究経験を振り返り未来を考える Reviewed

    情報・システムソサイエティ誌   Vol. 27 ( 1 )   2022.5

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  135. Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes Reviewed

    Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

    Proc. SPIE 12033     2022.3

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  136. Spatial label smoothing via aleatoric uncertainty for bleeding region segmentation from laparoscopic videos Reviewed

    Jie Qiu, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Nobuyoshi Takeshita, Masaaki Ito, Kensaku Mori

    Proc. SPIE 12032     2022.3

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  137. Effective hyperparameter optimization with proxy data for multi-organ segmentation Reviewed

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

    Proc. SPIE 12032     2022.3

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  138. Coarse-to-fine cascade framework for cross-modality super-resolution on clinical/micro CT dataset, Reviewed

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

    Proc. SPIE 12032     2022.3

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  139. Bronchial orifice tracking-based branch level estimation for bronchoscopic navigation Reviewed

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

    Proc. SPIE 12034     2022.3

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  140. Taking full advantage of uncertainty estimation: an uncertainty-assisted two-stage pipeline for multi-organ segmentation Reviewed

    Zhou Zheng, Masahiro Oda, Kazunari Misawa, Kensaku Mori

    Proc. SPIE 12033     2022.3

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  141. Multiclass prediction for improving intestine segmentation on non-fecal-tagged CT volume Reviewed

    Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Aitaro Takimoto, Akinari,Hinoki, Hiroo Uchida, Kojiro Suzuki, Masahiro Oda, Kensaku Mori

    Proc. SPIE 12033     2022.3

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  142. Self-supervised depth estimation with uncertainty-weight joint loss function based on laparoscopic videos Reviewed

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

    Proc. SPIE 12034     2022.3

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  143. Size-reweighted cascaded fully convolutional network for substantia nigra segmentation from T2 MRI Reviewed

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

    Proc. SPIE 12032     2022.3

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  144. Substantia nigra analysis by tensor decomposition of T2-weighted images for Parkinson’s disease diagnosis Invited Reviewed

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

    Proc. SPIE 12032     2022.3

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  145. 人工知能(AI)最新動向 学会発表を中心に(2)-Digital Poster発表を中心に

    森 健策

    インナービジョン   Vol. 37 ( 2 ) page: 30 - 31   2022.2

  146. 医用画像処理による人体構造の解析とその診断治療への応用 ~ 30年間の医用画像研究経験を振り返り未来を考える ~

    森 健策

    電子情報通信学会技術研究報告(MI), MI2021-74   Vol. 121 ( 347 ) page: 127 - 132   2022.1

  147. 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

    電子情報通信学会技術研究報告(MI), MI2021-57   Vol. 121 ( 347 ) page: 49 - 54   2022.1

  148. 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

    電子情報通信学会技術研究報告(MI), MI2021-63   Vol. 121 ( 347 ) page: 86 - 87   2022.1

  149. 大規模腹腔鏡動画像データベース構築に向けたオンラインアノテーションツールの開発

    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

    電子情報通信学会技術研究報告(MI), MI2021-65   Vol. 121 ( 347 ) page: 86 - 87   2022.1

  150. 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 Invited Reviewed

    呉 運恒, 小田 昌宏, 林 雄一郎, 武部 貴則, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 121 ( 347 ) page: 174 - 179   2022.1

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

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

    Medical Physics   Vol. 48 ( 11 ) page: 7215 - 7227   2021.11

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    DOI: 10.1002/mp.15192

  152. 胸腔鏡下手術におけるパノラマビジョンリングの基礎開発 Reviewed

    北坂 孝幸,林 雄一郎,中村 彰太,芳川 豊史,森 健策,中井 剛,中井 康博

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 318   2021.11

  153. 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 Reviewed

    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

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 217 - 218   2021.11

  154. 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 Reviewed

    椎名 健, 小田 紘久, 鄭 通, 中村 彰太, 林 雄一郎, 小田 昌宏, 森 健策

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 219 - 220   2021.11

  155. 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 Reviewed

    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

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 243 - 244   2021.11

  156. 腹腔鏡下胃切除術支援のための腹腔鏡映像からの術中操作の予測に関する初期検討 Reviewed

    林 雄一郎, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 248   2021.11

  157. 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 Reviewed

    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

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 265 - 266   2021.11

  158. MRI 画像からの大脳基底核のAIセグメンテーション―Skip Connection による抽出精度向上の検討 Reviewed

    杉野貴明,金 太一,斎藤 季,川瀬 利弘,小野木 真哉,齊藤 延人,森 健策, 中島 義和

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 286   2021.11

  159. CT 像からの腸管領域抽出改善に関する基礎的検討 Reviewed

    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

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 287 - 288   2021.11

  160. 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 Reviewed

    出口 智也,林 雄一郎,北坂 孝幸,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30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 299 - 300   2021.11

  161. 腹腔鏡下胃切除術の手術ナビゲーションにおける位置合わせ誤差の補正に関する検討 Reviewed

    林 雄一郎, 三澤 一成,森 健策

    日本コンピュータ外科学会誌 第30回日本コンピュータ外科学会大会特集号   Vol. 23 ( 4 ) page: 301 - 302   2021.11

  162. 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予稿集     page: 65 - 67   2021.10

  163. VR Organ Puzzle: A Virtual Reality Application for the Education of Human Anatomy

    Siqi LI, Yuichiro HAYASHI,Michitaka FUJIWARA, Masahiro ODA, Kensaku MORI

        page: 489 - 491   2021.10

  164. 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

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  165. 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

        page: 394 - 400   2021.10

  166. 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予稿集     page: 374 - 377   2021.10

  167. 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予稿集     page: 309 - 317   2021.10

  168. 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予稿集     page: 270 - 272   2021.10

  169. 3D Kidney Tumor Semantic Segmentation using Cascaded Convolutional Networks Invited Reviewed

    第40回日本医用画像工学会大会予稿集     page: 243 - 248   2021.10

  170. 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,

    出口 智也, 林 雄一郎, 北坂 孝幸, 小田 昌宏,1 三澤 一成, 森 健策

    第40回日本医用画像工学会大会予稿集     page: 239 - 241   2021.10

  171. 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,1 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予稿集     page: 235 - 241   2021.10

  172. Vascular Structure Segmentation in Stereomicroscope Image

    Yunheng WU, Masahiro ODA, Yuichiro HAYASHI, Takanori TAKEBE, Kensaku MORI

        page: 229 - 234   2021.10

  173. 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

        page: 199 - 201   2021.10

  174. Improving Classification Accuracy of Hands' Bone Marrow Edema by Transfer Learning

    Dongping PAN, Masahiro ODA, Kou KATAYAMA, Takanobu Okubo, Kensaku MORI

        page: 150 - 157   2021.10

  175. 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予稿集     page: 129 - 131   2021.10

  176. Self-attention Class Balanced DenseNet_LSTM framework for Subarachnoid Hemorrhage CT image Classification on Extremely Imbalanced Brain CT Dataset

    第40回日本医用画像工学会大会予稿集     page: 69 - 75   2021.10

  177. VR Organ Puzzle: A Virtual Reality Application for the Education of Human Anatomy

    Siqi LI, Yuichiro HAYASHI,Michitaka FUJIWARA, Masahiro ODA, Kensaku MORI

        page: 493 - 498   2021.10

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

    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

    LNCS12969     page: 101 - 110   2021.9

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  179. Intestine segmentation with small computational cost for diagnosis assistance of ileus and intestinal obstruction Invited Reviewed

    Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Masahiro Oda, Kensaku Mori

    LNCS 12969     page: 3 - 12   2021.9

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

    Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masahiro Oda, Kensaku Mori

    LNCS12965     page: 24 - 33   2021.9

  181. 泌尿器科領域における画像処理

    森 健策

    泌尿器科   Vol. 14 ( 2 ) page: 213 - 220   2021.8

  182. Can artificial intelligence help to detect dysplasia in patients with ulcerative colitis? Invited International journal

    Yasuharu Maeda, Shin-Ei Kudo, Noriyuki Ogata, Masashi Misawa, Yuichi Mori, Kensaku Mori, Kazuo Ohtsuka

    Endoscopy   Vol. 53 ( 07 ) page: E273 - E274   2021.7

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    DOI: 10.1055/a-1261-2944

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  183. Micro-CT-assisted cross-modality super-resolution of clinical CT: utilization of synthesized training dataset Reviewed

    T. Zheng, H. Oda, S. Nakamura, M. Mori, H. Takabatake, H. Natori, M. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 12 - 14   2021.6

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

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

    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

  185. AIによる内視鏡外科手術支援と開発基盤としての手術動画データベース構築 Invited Reviewed

    竹下 修由, 森 健策, 伊藤 正昭

    消化器外科   Vol. 44 ( 7 ) page: 1159 - 1166   2021.6

  186. Three-dimensional surgical plan printing for assisting liver surgery, Reviewed

    Y. Hayashi, T. Igami, Y. Nakamura, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 104 - 106   2021.6

  187. COVID-19 lung infection and normal region segmentation from CT volumes using FCN with local and global spatial feature encoder Reviewed

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 19 - 20   2021.6

  188. Experimental evaluation of loss functions in YOLO-v3 training for the perforation detection and localization in colonoscopic videos Reviewed

    K. Jiang, H. Itoh, M. Oda, T. Okumura, Y. Mori, M. Misawa, T. Hayashi, S. E. Kudo, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 74 - 75   2021.6

  189. Blood vessel regions segmentation from laparoscopic videos using fully convolutional networks with multi field of view input Reviewed

    K. Mori, S. Morimitsu, S. Yamamoto, T. Ozawa, T. Kitasaka, Y. Hayashi, M. Oda, M. Ito, N. Takeshita, K. Misawa

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 56 - 57   2021.6

  190. `Intestine segmentation combining Watershed transformation and machine learning-based distance map estimation Reviewed

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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 89 - 90   2021.6

  191. Real-time deformation simulation of hollow organs based on XPBD with small time steps and air mesh for surgical simulation Reviewed

    S. Li, Y. Hayashi, M. Oda, K. Misawa, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 21 - 25   2021.6

  192. Spatial Information Considered Module based on Attention Mechanism for Self-Supervised Depth Estimation from Laparoscopic Image Pairs Reviewed

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

    nternational Journal of Computer Assisted Radiology and Surgery   Vol. 16 ( sup.1 ) page: 45 - 46   2021.6

  193. 機械学習によるCOVID-19症例CT画像の診断支援 Reviewed

    森 健策

    映像情報メディア学会誌   Vol. 75 ( 3 ) page: 326 - 329   2021.5

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

    Masashi Misawa, Shin-Ei Kudo, Yuichi Mori, Kinichi Hotta, Kazuo Ohtsuka, Takahisa Matsuda, Shoichi Saito, Toyoki Kudo, Toshiyuki Baba, Fumio Ishida, Hayato Itoh, Masahiro Oda, Kensaku Mori

    Gastrointestinal endoscopy   Vol. 93 ( 4 ) page: 960 - 967   2021.4

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    BACKGROUND AND AIMS: Artificial intelligence (AI)-assisted polyp detection systems for colonoscopic use are currently attracting attention because they may reduce the possibility of missed adenomas. However, few systems have the necessary regulatory approval for use in clinical practice. We aimed to develop an AI-assisted polyp detection system and to validate its performance using a large colonoscopy video database designed to be publicly accessible. METHODS: To develop the deep learning-based AI system, 56,668 independent colonoscopy images were obtained from 5 centers for use as training images. To validate the trained AI system, consecutive colonoscopy videos taken at a university hospital between October 2018 and January 2019 were searched to construct a database containing polyps with unbiased variance. All images were annotated by endoscopists according to the presence or absence of polyps and the polyps' locations with bounding boxes. RESULTS: A total of 1405 videos acquired during the study period were identified for the validation database, 797 of which contained at least 1 polyp. Of these, 100 videos containing 100 independent polyps and 13 videos negative for polyps were randomly extracted, resulting in 152,560 frames (49,799 positive frames and 102,761 negative frames) for the database. The AI showed 90.5% sensitivity and 93.7% specificity for frame-based analysis. The per-polyp sensitivities for all, diminutive, protruded, and flat polyps were 98.0%, 98.3%, 98.5%, and 97.0%, respectively. CONCLUSIONS: Our trained AI system was validated with a new large publicly accessible colonoscopy database and could identify colorectal lesions with high sensitivity and specificity. (Clinical trial registration number: UMIN 000037064.).

    DOI: 10.1016/j.gie.2020.07.060

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  195. Contrastive Learningを用いた肺野CT画像からCOVID-19の自動判定 Invited Reviewed

    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

    電子情報通信学会技術研究報告(MI)   Vol. 120 ( 432 ) page: 82 - 86   2021.3

  196. 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 Invited Reviewed

    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

    電子情報通信学会技術研究報告(MI)   Vol. 120 ( 431 ) page: 172 - 175   2021.3

  197. 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 Invited Reviewed

    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

    電子情報通信学会技術研究報告(MI)   Vol. 120 ( 431 ) page: 176 - 181   2021.3

  198. Artificial Intelligence System to Determine Risk of T1 Colorectal Cancer Metastasis to Lymph Node. Invited Reviewed International journal

    Shin-Ei Kudo, Katsuro Ichimasa, Benjamin Villard, Yuichi Mori, Masashi Misawa, Shoichi Saito, Kinichi Hotta, Yutaka Saito, Takahisa Matsuda, Kazutaka Yamada, Toshifumi Mitani, Kazuo Ohtsuka, Akiko Chino, Daisuke Ide, Kenichiro Imai, Yoshihiro Kishida, Keiko Nakamura, Yasumitsu Saiki, Masafumi Tanaka, Shu Hoteya, Satoshi Yamashita, Yusuke Kinugasa, Masayoshi Fukuda, Toyoki Kudo, Hideyuki Miyachi, Fumio Ishida, Hayato Itoh, Masahiro Oda, Kensaku Mori

    Gastroenterology   Vol. 160 ( 4 ) page: 1075 - 1084.e2   2021.3

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    BACKGROUND & AIMS: In accordance with guidelines, most patients with T1 colorectal cancers (CRC) undergo surgical resection with lymph node dissection, despite the low incidence (∼10%) of metastasis to lymph nodes. To reduce unnecessary surgical resections, we used artificial intelligence to build a model to identify T1 colorectal tumors at risk for metastasis to lymph node and validated the model in a separate set of patients. METHODS: We collected data from 3134 patients with T1 CRC treated at 6 hospitals in Japan from April 1997 through September 2017 (training cohort). We developed a machine-learning artificial neural network (ANN) using data on patients' age and sex, as well as tumor size, location, morphology, lymphatic and vascular invasion, and histologic grade. We then conducted the external validation on the ANN model using independent 939 patients at another hospital during the same period (validation cohort). We calculated areas under the receiver operator characteristics curves (AUCs) for the ability of the model and US guidelines to identify patients with lymph node metastases. RESULTS: Lymph node metastases were found in 319 (10.2%) of 3134 patients in the training cohort and 79 (8.4%) of /939 patients in the validation cohort. In the validation cohort, the ANN model identified patients with lymph node metastases with an AUC of 0.83, whereas the guidelines identified patients with lymph node metastases with an AUC of 0.73 (P < .001). When the analysis was limited to patients with initial endoscopic resection (n = 517), the ANN model identified patients with lymph node metastases with an AUC of 0.84 and the guidelines identified these patients with an AUC of 0.77 (P = .005). CONCLUSIONS: The ANN model outperformed guidelines in identifying patients with T1 CRCs who had lymph node metastases. This model might be used to determine which patients require additional surgery after endoscopic resection of T1 CRCs. UMIN Clinical Trials Registry no: UMIN000038609.

    DOI: 10.1053/j.gastro.2020.09.027

    DOI: 10.1053/j.gastro.2020.09.027

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  199. Unsupervised segmentation of COVID-19 infected lung clinical CT volumes using image inpainting and representation learning Reviewed

    Tong Zheng, Masahiro Oda, Chenglong Wang, Takayasu Moriya, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

    Proc. SPIE 11596, Medical Imaging, 2021: Image Processing     page: 115963F-1 - 6   2021.2

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    DOI: 10.1117/12.2580641

  200. Extremely imbalanced subarachnoid hemorrhage detection based on enseNet-LSTM network with class-balanced loss and transfer learning Reviewed

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

    Proceedings Volume 11597, Medical Imaging 2021: Computer-Aided Diagnosis     page: 115971Z   2021.2

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    DOI: 10.1117/12.2582088

  201. Single-shot three-dimensional reconstruction for colonoscopic image analysis Reviewed

    Hayato Itoh, Masahiro Oda, Yuichi Mori, Masashi Misawa, Shin-ei Kudo, Kinnichi Hotta, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    Proc. SPIE 11598, Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling     page: 115980E-1 - 6   2021.2

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    DOI: 10.1117/12.2582660

  202. Intestinal region reconstruction of ileus cases from 3D CT images based on graphical representation and its visualization Reviewed

    Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Yudai Tamada, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, Kensaku Mori

    Proc.SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis     2021.2

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    DOI: 10.1117/12.2581261

  203. Lung infection and normal region segmentation from CT volumes of COVID-19 cases Reviewed

    Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Kensaku Mori

    Proc. SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis     page: 115972X-1 - 6   2021.2

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    DOI: 10.1117/12.2582066

  204. Extraction of lung and lesion regions from COVID-19 CT volumes using 3D fully convolutional networks Reviewed

    Yuichiro Hayashi, Masahiro Oda, Chen Shen, Masahiro Hashimoto, Yoshito Otake, Toshiaki Akashi, Kensaku Mori

    Proc.SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis     page: 115972A-1 - 6   2021.2

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    DOI: 10.1117/12.2581818

  205. 人工知能(AI)最新動向 AI研究から見たRSNA-AIの広がりを感じる大会 Invited

    森 健策

    インナービジョン   Vol. 36 ( 2 ) page: 25 - 26   2021.2

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  206. 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

    小田 昌宏, 森 健策

    C-press   Vol. 120   page: 5 - 6   2021.2

  207. COVID-19診断支援AI開発における名古屋大学の取り組み

    小田 昌宏, 鄭 通, 林 雄一郎, 森 健策

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

  208. New method for the assessment of perineural invasion from perihilar cholangiocarcinoma Reviewed

    Hiroshi Tanaka, Tsuyoshi Igami, Yoshie Shimoyama, Tomoki Ebata, Yukihiro Yokoyama, Kensaku Mori, Masato Nagino,

    Surgery Today   Vol. 51 ( 2 ) page: 136 - 143   2021.1

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    DOI: 10.1007/s00595-020-02071-x

  209. Current status and future perspective on artificial intelligence for lower endoscopy. Invited International journal

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

    Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society   Vol. 33 ( 2 ) page: 273 - 284   2021.1

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    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 non-experts 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.

    DOI: 10.1111/den.13847

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  210. Dense-layer-based YOLO-v3 for detection and localization of colon perforations Invited Reviewed

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

    Medical Imaging 2021: Computer-Aided Diagnosis   Vol. 11597   page: 115971A-1 - 6   2021

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    DOI: 10.1117/12.2582300

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  211. [総論]AI時代を見据えた消化器外科手術 AIによる大腸T2癌リンパ節転移予測 Invited Reviewed

    中原 健太, 石田 文生, 一政 克朗, 森 悠一, 三澤 将史, 澤田 成彦, 工藤 進英, Villard Ben, 伊東 隼人, 森 健策

    日本消化器外科学会総会   Vol. 75回   page: WS15 - 6   2020.12

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  212. Improving contrast and spatial resolution in crystal analyzer based x ray dark field imaging Reviewed

    Masami Ando Yuki Nakao Ge Jin Hiroshi Sugiyama Naoki Sunaguchi Yongjin Sung Yoshifumi Suzuki Yong Sun Michio Tanimoto Katsuhiro Kawashima Tetsuya Yuasa Kensaku Mori Shu Ichihara Rajiv Gupta,

    Medical Physics   Vol. 47 ( 11 ) page: 5505 - 5513   2020.11

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    DOI: 10.1002/mp.14442

  213. 多元計算解剖モデルと人工知能に基づく診断治療支援 Invited Reviewed

    森 健策

    映像情報メディア学会誌   Vol. 74 ( 6 ) page: 909-915   2020.11

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  214. Preliminary study of Loss-Function Design for Detection and Localization of Perforations with YOLO-v3 in Colonoscopic Images

      Vol. 22 ( 4 ) page: 348 - 349   2020.11

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  215. 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

    日本コンピュータ外科学会誌 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 282 - 284   2020.11

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  216. 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

    日本コンピュータ外科学会誌 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 285 - 286   2020.11

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  217. 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

    日本コンピュータ外科学会誌 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 287 - 288   2020.11

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  218. 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

    日本コンピュータ外科学会誌 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 294 - 295   2020.11

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  219. 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

    日本コンピュータ外科学会誌 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 296 - 297   2020.11

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  220. 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 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 306 - 307   2020.11

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  221. 呼吸器外科における仮想胸腔鏡像による手術ナビゲーションシステムを用いた手術支援の検討

    林 雄一郎, 中村 彰太,森 健策

    日本コンピュータ外科学会誌 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 337   2020.11

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  222. 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

    日本コンピュータ外科学会誌 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 338 - 339   2020.11

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  223. 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 第29回日本コンピュータ外科学会大会特集号   Vol. 22 ( 4 ) page: 346 - 347   2020.11

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  224. Cost savings in colonoscopy with artificial intelligence-aided polyp diagnosis: an add-on analysis of a clinical trial (with video). Invited Reviewed International journal

    Yuichi Mori, Shin-Ei Kudo, James E East, Amit Rastogi, Michael Bretthauer, Masashi Misawa, Masau Sekiguchi, Takahisa Matsuda, Yutaka Saito, Hiroaki Ikematsu, Kinichi Hotta, Kazuo Ohtsuka, Toyoki Kudo, Kensaku Mori

    Gastrointestinal endoscopy   Vol. 92 ( 4 ) page: 905 - 911   2020.10

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    BACKGROUND AND AIMS: Artificial intelligence (AI) is being implemented in colonoscopy practice, but no study has investigated whether AI is cost saving. We aimed to quantify the cost reduction using AI as an aid in the optical diagnosis of colorectal polyps. METHODS: This study is an add-on analysis of a clinical trial that investigated the performance of AI for differentiating colorectal polyps (ie, neoplastic versus non-neoplastic). We included all patients with diminutive (≤5 mm) rectosigmoid polyps in the analyses. The average colonoscopy cost was compared for 2 scenarios: (1) a diagnose-and-leave strategy supported by the AI prediction (ie, diminutive rectosigmoid polyps were not removed when predicted as non-neoplastic), and (2) a resect-all-polyps strategy. Gross annual costs for colonoscopies were also calculated based on the number and reimbursement of colonoscopies conducted under public health insurances in 4 countries. RESULTS: Overall, 207 patients with 250 diminutive rectosigmoid polyps (104 neoplastic, 144 non-neoplastic, and 2 indeterminate) were included. AI correctly differentiated neoplastic polyps with 93.3% sensitivity, 95.2% specificity, and 95.2% negative predictive value. Thus, 105 polyps were removed and 145 were left under the diagnose-and-leave strategy, which was estimated to reduce the average colonoscopy cost and the gross annual reimbursement for colonoscopies by 18.9% and US$149.2 million in Japan, 6.9% and US$12.3 million in England, 7.6% and US$1.1 million in Norway, and 10.9% and US$85.2 million in the United States, respectively, compared with the resect-all-polyps strategy. CONCLUSIONS: The use of AI to enable the diagnose-and-leave strategy results in substantial cost reductions for colonoscopy.

    DOI: 10.1016/j.gie.2020.03.3759

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    PubMed

  225. 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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    DOI: 10.1002/mp.14372

  226. 名古屋大学スーパーコンピュータ「不老」における医用画像処理

    大島 聡史, 小田 昌宏, 片桐 孝洋, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 120 ( 156 ) page: 69 - 74   2020.9

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  227. 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

        page: 142 - 147   2020.9

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  228. 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予稿集     page: 163 - 167   2020.9

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  229. 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

        page: 168 - 172   2020.9

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  230. 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予稿集     page: 181 - 184   2020.9

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  231. Preliminary Study on Classification of Interstitial Cystitis Using Cystoscopy Images

    Tao Chu, Masahiro Oda, Akira Furuta, Tokunori Yamamoto, Kensaku Mori

        page: 186 - 191   2020.9

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  232. 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予稿集     page: 230 - 233   2020.9

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  233. 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予稿集     page: 246 - 249   2020.9

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  234. 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予稿集     page: 268 - 271   2020.9

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  235. Cross-phase CT Image Registration Using Convolutional Neural Network

    Tao Hu, Masahiro Oda, Yuichiro Hayashi, Zhongyang Lu, Kanako Kunishishima Kumamaru, Shigeki Aoki, Kensaku Mori

        page: 276 - 280   2020.9

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  236. Unsupervised 3D Super-resolution of Clinical CT Volumes by Utilizing Multi-axis 2D Super-resolution

    第39回日本医用画像工学会大会予稿集     page: 377 - 384   2020.9

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  237. Preliminary Study on Classification of Hands' Bone Marrow Edema Using X-ray Images

    Dongping Pan, Masahiro Oda, Kou Katayama, Takanobu Okubo, Kensaku Mori

        page: 488 - 493   2020.9

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  238. 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予稿集     page: 563 - 568   2020.9

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  239. 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

        page: 602 - 606   2020.9

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  240. 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予稿集     page: 611 - 615   2020.9

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  241. ニューラルネットワークとSpherical K-meansを用いた胃壁マイクロCT像からの層構造および腫瘍抽出の検討

    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

    電子情報通信学会技術研究報告(MI)   Vol. 120 ( 156 ) page: 1 - 6   2020.9

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  242. 泌尿器科画像診断に用いられるAI技術とその応用

    森 健策

    泌尿器外科   Vol. 33 ( 6 ) page: 557-561   2020.6

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  243. Detecting ganglion cells on virtual slide images: Macroscopic masking by superpixel Reviewed

    H. Oda, Y. Tamada, K. Nishio, T. Kitasaka, H. Amano, K. Chiba, A. Hinoki, H. Uchida, M. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 15 ( 1 ) page: S169 - S170   2020.6

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  244. An Application of Multi-organ Segmentation from Thick-slice Abdominal CT Volumes using Transfer Learning Reviewed

    C. Shen, M. Oda, H. Roth, H. Oda, Y. Hayashi, K. Misawa, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 15 ( 1 ) page: S17 - S18   2020.6

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  245. Virtual cleansing by unpaired image translation of intestines for detecting obstruction Reviewed

    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

    International Journal of Computer Assisted Radiology and Surgery   Vol. 15 ( 1 ) page: S21 - S22   2020.6

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  246. TinyLoss: loss function for tiny image difference evaluation and its application to unpaired non-contrast to contrast abdominal CT estimation Reviewed

    M. Oda, T. Hu, K. K. Kumamaru, T. Akashi, S. Aoki, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 15 ( 1 ) page: S25 - S26   2020.6

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  247. SR-CycleGAN V2: CycleGAN-based unsupervised superresolution with pixel-shuffling Reviewed

    T. Zheng, H. Oda, T. Moriya, T. Sugino, S. Nakamura, M. Oda, M. Mori, H. Takabatake, H. Natori, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 15 ( 1 ) page: S27 - S28   2020.6

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  248. Blood vessel segmentation from laparoscopic video using ConvLSTM U-Net

    S. Morimitsu, S. Yamamoto, T. Ozawa, T. Kitasaka, Y. Hayashi, M. Oda, M. Ito, N. Takeshita, K. Misawa, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 15 ( 1 ) page: S63 - S64   2020.6

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  249. Extraction of blood vessel regions in liver from CT volumes using fully convolutional networks for computer assisted liver surgery Reviewed

    Y. Hayashi, C. Shen, T. Igami, M. Nagino, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 15 ( 1 ) page: S152 - S153   2020.6

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  250. AIによるSSA/Pの超拡大内視鏡診断 Invited Reviewed

    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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  251. バーチャル・リアリティ手術シュミレーター(VRS)の意義と今後の展望

    藤原 道隆, 林 雄一郎, 高見 秀樹, 田中 千恵, 森 健策, 小寺 泰弘

    臨床外科   Vol. 75 ( 4 ) page: 476 - 482   2020.4

  252. Cardiac fiber tracking on super high-resolution CT images: a comparative study. Invited International journal

    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 (Bellingham, Wash.)   Vol. 7 ( 2 ) page: 026001 - 026001   2020.3

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    Purpose: High-resolution cardiac imaging and fiber analysis methods are required to understand cardiac anatomy. Although refraction-contrast x-ray CT (RCT) has high soft tissue contrast, it cannot be commonly used because it requires a synchrotron system. Microfocus x-ray CT ( μ CT ) is another commercially available imaging modality. Approach: We evaluate the usefulness of μ CT for analyzing fibers by quantitatively and objectively comparing the results with RCT. To do so, we scanned a rabbit heart by both modalities with our original protocol of prepared materials and compared their image-based analysis results, including fiber orientation estimation and fiber tracking. Results: Fiber orientations estimated by two modalities were closely resembled under the correlation coefficient of 0.63. Tracked fibers from both modalities matched well the anatomical knowledge that fiber orientations are different inside and outside of the left ventricle. However, the μ CT volume caused incorrect tracking around the boundaries caused by stitching scanning. Conclusions: Our experimental results demonstrated that μ CT scanning can be used for cardiac fiber analysis, although further investigation is required in the differences of fiber analysis results on RCT and μ CT .

    DOI: 10.1117/1.JMI.7.2.026001

    Web of Science

    Scopus

    PubMed

    CiNii Research

  253. 3Dプリンティングの最新動向 Invited

    森 健策

    インナービジョン   Vol. 35 ( 2 ) page: 36-37   2020.2

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  254. 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

    Medical Imaging 2020: Image Processing   Vol. 11313   2020.2

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

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

    Medical Imaging 2020: Image Processing   Vol. 11314   2020.2

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

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

    Medical Imaging 2020: Image Processing   Vol. 11314   2020.2

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

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

    Medical Imaging 2020: Image Processing   Vol. 11315   2020.2

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

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

    Medical Imaging 2020: Image Processing   Vol. 11314   2020.2

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  259. Organ segmentation from full-size CT images using memory-efficient FCN Reviewed

    Chenglong Wang, Masahiro Oda, Kensaku Mori

    Medical Imaging 2020: Image Processing   Vol. 11314   2020.2

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  260. 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

    Medical Imaging 2020: Image Processing   Vol. 11313   2020.2

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

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

    Medical Imaging 2020: Image Processing   Vol. 11314   2020.2

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  262. 仮想腹腔鏡画像生成と深層学習による腹腔鏡画像からの術具領域セグメンテーション

    小澤 卓也, 林 雄一郎, 小田 紘久, 小田 昌宏, 北坂 孝幸, 竹下 修由, 伊藤 雅昭, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 119 ( 399 ) page: 129 - 134   2020.1

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  263. 腹腔鏡下手術支援のためのU-Netに基づく腹腔鏡動画像からの出血領域の推定

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

    電子情報通信学会技術研究報告(MI)   Vol. 119 ( 399 ) page: 209 - 214   2020.1

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  264. MICCAI 2019参加報告

    小田 昌宏, 伊東 隼人, 宮内 翔子, 諸岡 健一, 松崎 博貴, 花岡 昇平, 古川 亮, 増谷 佳孝, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 119 ( 399 ) page: 219 - 226   2020.1

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  265. CycleGANによる腸管電子洗浄とその腸管閉塞部位検出への応用

    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

    電子情報通信学会技術研究報告(MI)   Vol. 119 ( 399 ) page: 243 - 248   2020.1

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  266. 臨床肺CT画像と切除肺マイクロCT画像の非剛体位置合わせ手法の検討

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

    電子情報通信学会技術研究報告(MI)   Vol. 119 ( 399 ) page: 249 - 254   2020.1

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

    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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  268. Automatic Quantitative Analysis of Kidney Tumor Using 3D Fully Convolutional Network

    Chenglong Wang, Masahiro Oda, Yuichiro Hayashi, Naoto Sassa, Tokunori Yamamoto, Kensaku Mori

    RSNA2019     page: UR002-EB-X   2019.12

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  269. Technique for Improving Accuracy of Deep Learning-based Multi-Organ Segmentation from CT Volumes

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

    RSNA2019     page: N021-EC-X   2019.12

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  270. Micro Lung Cancer Analysis Based on Micro CT Imaging Using Generative Adversarial Network

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

    RSNA2019     page: CH007-EC-X   2019.12

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  271. 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

    RSNA2019     page: AI020-EB-X   2019.12

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  272. 大腸肛門病理学におけるAI利用の将来像

    森 健策

    日本大腸肛門病学学術集会 抄録号     page: A17   2019.10

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  273. 機械学習を用いた医療支援

    森 健策

    第84回日本泌尿器気学会東部総会, プログラム 抄録集     page: 123   2019.10

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

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

    MICCAI 2019   Vol. LNCS 11769   page: 240-248   2019.10

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  275. Tubular Structure Segmentation Using Spatial Fully Connected Network With Radial Distance Loss for 3D Medical images

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

    MICCAI 2019   Vol. LNCS 11769   page: 348-356   2019.10

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  276. Intelligent Image Synthesis to Attack a egmentation CNN Using Adversarial Learning

    Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert

    MICCAI 2019   Vol. LNCS 11827   page: 90-99   2019.10

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

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

    MICCAI 2019   Vol. LNCS 11840   page: 104-114   2019.10

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  278. 胸部領域AIの歴史と今後-歴史的研究を振り返りながら今後を展望する-

    森 健策

    臨床画像   Vol. 35 ( 10 ) page: 1139-1149   2019.10

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

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

    MICCAI 2019 Healthcare Technology Letters     2019.10

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    DOI: 10.1049/htl.2019.0071

  280. Stable Polyp-Scene Classification via Subsampling and Residual Learning from an Imbalanced Large Dataset

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

    MICCAI 2019 Healthcare Technology Letters     page: 1-6   2019.10

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    DOI: 10.1049/htl.2019.0079

  281. 人工知能時代の医療を考える

    森 健策

    EAJ NEWS「AI×医療」特集号   ( 181 ) page: 6-8   2019.10

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

    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 ( 10642 ) page: 1-13   2019.10

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    DOI: 10.1016/j.compmedimag.2019.101642

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

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

    LNCS11769     page: 240-248   2019.10

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  284. Tubular Structure Segmentation Using Spatial Fully Connected Network With Radial Distance Loss for 3D Medical images

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

    LNCS11769     page: 348-356   2019.10

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  285. Intelligent Image Synthesis to Attack a segmentation CNN Using Adversarial Learning

    Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert,

    LNCS11827     page: 90-99   2019.10

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

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

    LNCS 11840     page: 104-114   2019.10

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  287. Artificial Intelligence-assisted System Improves Endoscopic Identification of Colorectal Neoplasms. Reviewed International journal

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

    Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association   Vol. 18 ( 8 ) page: 1874 - 1881   2019.9

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    BACKGROUND & AIMS: Precise optical diagnosis of colorectal polyps could improve the cost-effectiveness of colonoscopy and reduce polypectomy-related complications. However, it is difficult for community-based non-experts to obtain sufficient diagnostic performance. Artificial intelligence-based systems have been developed to analyze endoscopic images; they identify neoplasms with high accuracy and low interobserver variation. We performed a multi-center study to determine the diagnostic accuracy of EndoBRAIN, an artificial intelligence-based system that analyzes cell nuclei, crypt structure, and microvessels in endoscopic images, in identification of colon neoplasms. METHODS: The EndoBRAIN system was initially trained using 69,142 endocytoscopic images, taken at 520-fold magnification, from patients with colorectal polyps who underwent endoscopy at 5 academic centers in Japan from October 2017 through March 2018. We performed a retrospective comparative analysis of the diagnostic performance of EndoBRAIN vs that of 30 endoscopists (20 trainees and 10 experts); the endoscopists assessed images from 100 cases produced via white-light microscopy, endocytoscopy with methylene blue staining, and endocytoscopy with narrow-band imaging. EndoBRAIN was used to assess endocytoscopic, but not white-light, images. The primary outcome was the accuracy of EndoBrain in distinguishing neoplasms from non-neoplasms, compared with that of endoscopists, using findings from pathology analysis as the reference standard. RESULTS: In analysis of stained endocytoscopic images, EndoBRAIN identified colon lesions with 96.9% sensitivity (95% CI, 95.8%-97.8%), 100% specificity (95% CI, 99.6%-100%), 98% accuracy (95% CI, 97.3%-98.6%), a 100% positive-predictive value (95% CI, 99.8%-100%), and a 94.6% negative-predictive (95% CI, 92.7%-96.1%); these values were all significantly greater than those of the endoscopy trainees and experts. In analysis of narrow-band images, EndoBRAIN distinguished neoplastic from non-neoplastic lesions with 96.9% sensitivity (95% CI, 95.8-97.8), 94.3% specificity (95% CI, 92.3-95.9), 96.0% accuracy (95% CI, 95.1-96.8), a 96.9% positive-predictive value, (95% CI, 95.8-97.8), and a 94.3% negative-predictive value (95% CI, 92.3-95.9); these values were all significantly higher than those of the endoscopy trainees, sensitivity and negative-predictive value were significantly higher but the other values are comparable to those of the experts. CONCLUSIONS: EndoBRAIN accurately differentiated neoplastic from non-neoplastic lesions in stained endocytoscopic images and endocytoscopic narrow-band images, when pathology findings were used as the standard. This technology has been authorized for clinical use by the Japanese regulatory agency and should be used in endoscopic evaluation of small polyps more widespread clinical settings. UMIN clinical trial no: UMIN000028843.

    DOI: 10.1016/j.cgh.2019.09.009

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  288. 人工知能による画像診断支援-どこまでできたか.そして,その先は?

    森 健策

    第46回 日本小児内視鏡研究会 プログラム・抄録集     page: 11   2019.7

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  289. Artificial intelligence and upper gastrointestinal endoscopy: Current status and future perspective. International journal

    Yuichi Mori, Shin-Ei Kudo, Hussein E N Mohmed, Masashi Misawa, Noriyuki Ogata, Hayato Itoh, Masahiro Oda, Kensaku Mori

    Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society   Vol. 31 ( 4 ) page: 378 - 388   2019.7

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    With recent breakthroughs in artificial intelligence, computer-aided diagnosis (CAD) for upper gastrointestinal endoscopy is gaining increasing attention. Main research focuses in this field include automated identification of dysplasia in Barrett's esophagus and detection of early gastric cancers. By helping endoscopists avoid missing and mischaracterizing neoplastic change in both the esophagus and the stomach, these technologies potentially contribute to solving current limitations of gastroscopy. Currently, optical diagnosis of early-stage dysplasia related to Barrett's esophagus can be precisely achieved only by endoscopists proficient in advanced endoscopic imaging, and the false-negative rate for detecting gastric cancer is approximately 10%. Ideally, these novel technologies should work during real-time gastroscopy to provide on-site decision support for endoscopists regardless of their skill; however, previous studies of these topics remain ex vivo and experimental in design. Therefore, the feasibility, effectiveness, and safety of CAD for upper gastrointestinal endoscopy in clinical practice remain unknown, although a considerable number of pilot studies have been conducted by both engineers and medical doctors with excellent results. This review summarizes current publications relating to CAD for upper gastrointestinal endoscopy from the perspective of endoscopists and aims to indicate what is required for future research and implementation in clinical practice.

    DOI: 10.1111/den.13317

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    CiNii Research

  290. Artificial intelligence and upper gastrointestinal endoscopy: current status and future perspective Reviewed

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

    Digestive endoscopy   Vol. 34 ( 4 ) page: 378-388   2019.7

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    DOI: 10.1111 den.13317

  291. 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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  292. 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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  293. 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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  294. 単眼腹腔鏡映像からの奥行き推定を利用した術具セグメンテーション

    鈴木 拓矢, 道満 恵介, 目加田 慶人, 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: OP1-11   2019.7

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  295. 大腸内視鏡(コロノスコピー)画像診断支援ソフトウェアの開発

    森 健策

    インナービジョン 2019年7月号   Vol. 34 ( 7 ) page: 45   2019.7

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  296. 内視鏡検査手術における超音波画像の利用-マルチモダリティ画像統合-

    森 健策

    計測と制御   Vol. 58 ( 7 ) page: 541-544   2019.7

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

        page: OP2-14   2019.7

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  298. 多元計算解剖学のその先にあるもの

    森 健策

    第38回日本医用画像工学会大会予稿集     page: SY2-5   2019.7

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  299. 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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  300. 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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  301. 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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  302. 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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  303. 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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  304. 開腹手術映像における遮蔽物除去システムの VR 化

    北坂 孝幸, 伊藤 幹也, 駒形 和哉, 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: OP4-10   2019.7

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  305. μ CT を用いた改良版 Cycle-GAN による臨床用 CT 像の超解像処理

    鄭 通, 小田 紘久, 守谷 享泰, 杉野 貴明, 中村 彰太, 小田 昌弘, 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: OP4-02   2019.7

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  306. 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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  307. 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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  308. Generative Adversarial Frameworks を用いた腹部 CT 像における非造影像からの造影像の推定

    小田 昌宏, 隈丸 加奈子, 青木 茂樹, 森 健策

    第38回日本医用画像工学会大会予稿集     page: OP3-07   2019.7

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  309. 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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  310. 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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  311. 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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  312. Artificial intelligence and upper gastrointestinal endoscopy: current status and future perspective Reviewed

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

    Digestive endoscopy   Vol. 34 ( 4 ) page: 378-388   2019.7

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  313. 医用画像AI

    森 健策

    医療機器学 第94回日本医療機器学会大会・学術集会   Vol. 89 ( 2 ) page: 107-108   2019.6

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  314. Automatic egistration of unordered point clouds for the study of abdominal organs and lymph node eformations

    B. Villard, K. Tachi, K. Misawa, M. Oda, K. Mori

    Computer Assisted Radiology 33rd International Congress and Exhibition CARS 2019     page: 0   2019.6

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  315. Semi-automated small intestine segmentation by fully convolutional networks and Hessian analysis

    K. Mori, H. Oda, T. Sugino, K. Nishio, K. Chiba, K. Oshima, T. Kitasaka, M. Oda, C. Shirota, A. Hinoki, H. Uchida

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s119-120   2019.6

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  316. 3D fully convolutional network-based head structure segmentation on multi-modal images from sparse annotation

    K. Mori, T. Sugino, H. Roth, M. Oda, T. Kin

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s120-121   2019.6

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  317. Non-contrast to contrasted abdominal CT volume regression using fully convolutional network

    M. Oda, K. K. Kumamaru, S. Aoki, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: 103-104   2019.6

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  318. Computer-based virtual clinical trial for pulmonary function diagnosis with ynamic chest radiograph

    R. Tanaka, E. Samei, W. P. Segars, E. Abadi, H. Roth, H. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s20-21   2019.6

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  319. Optical coherence tomography classification of multiple retinal diseases using DenseNet

    C. Wang, M. Oda, Y. Itoh, K.Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s69-70   2019.6

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  320. Artificial neural network for the prediction of colorectal lymph node metastasis

    B. Villard, H. Itoh, K. Ichimasa, Y. Mori, M. Misawa, M. Oda, S. Kudo, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019     page: 0   2019.6

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  321. Evaluation of squeeze and excitation fully convolutional networks for multi-organ segmentation

    C. Shen, F. Milletari, H. Roth, M. Oda, B. Villard, Y. Hayashi, K. Misawa, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s29-30   2019.6

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  322. Automatic segmentation of attention-aware artery region in laparoscopic colorectal surger

    S.Morimitsu, H. Itoh, T. Ozawa, H. Oda, T. Kitasaka, T. Sugino, Y. Hayashi, N. Takeshita, M. Ito, M. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s41-42   2019.6

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  323. Polyp-size determination method using short colonoscopic video clip information

    H. Itoh, Y. Mori, M. Misawa, M. Oda, S. E. Kudo, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s88-89   2019.6

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  324. 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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  325. 3D fully convolutional network-based head structure segmentation on multi-modal images from sparse annotation

    K. Mori, T. Sugino, H. Roth, M. Oda, T. Kin

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s120-121   2019.6

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  326. Computer-based virtual clinical trial for pulmonary function diagnosis with ynamic chest radiograph

    R. Tanaka, E. Samei, W. P. Segars, E. Abadi, H. Roth, H. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s20-21   2019.6

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  327. Automatic segmentation of attention-aware artery region in laparoscopic colorectal surger

    S.Morimitsu, H. Itoh, T. Ozawa, H. Oda, T. Kitasaka, T. Sugino, Y. Hayashi, N. Takeshita, M. Ito, M. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery CARS 2019   Vol. 14 ( 1 ) page: s41-42   2019.6

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  328. Automatic egistration of unordered point clouds for the study of abdominal organs and lymph node eformations

    B. Villard, K. Tachi, K. Misawa, M. Oda, K. Mori

    Computer Assisted Radiology 33rd International Congress and Exhibition CARS 2019     page: 0   2019.6

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  329. 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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  330. Radiomics nomogram for predicting the malignant potential of gastrointestinal stromal tumours preoperatively Reviewed

    Tao Chen, Zhenyuan Ning, Lili Xu, Xingyu Feng, Shuai Han, Holger R. Roth, Wei Xiong, Xixi Zhao, Yanfeng Hu, Hao Liu, Jiang Yu, Yu Zhang, Yong Li, Yikai Xu, Kensaku Mori, Guoxin Li

    European radiology   Vol. 29 ( 3 ) page: 1074-1082   2019.3

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  331. ビッグデータとAIの医療応用

    森 健策

    最新醫學   Vol. 74 ( 3 ) page: 20-28   2019.3

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  332. 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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  333. Scanning, registration, and fiber estimation of rabbit hearts using micro-focus and refraction-contrast x-ray CT

    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

    Proceedings of SPIE 10953, Medical Imaging 2019     page: 109531I-1-12   2019.2

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  334. Lung segmentation based on a deep learning approach for dynamic chest radiography

    Yuki Kitahara, Rie Tanaka, Holger Roth, Hirohisa Oda, Kensaku Mori, Kazuo Kasahara, Isao Matsumoto

    Proceedings of SPIE 10950, Medical Imaging 2019     page: 109503M-1-6   2019.2

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  335. Multiclass vertebral fracture classification using probability SVM with multi-feature selection

    Liyuan Zhang, Huamin Yang, Jiashi Zhao, Weili Shi, Yu Miao, Fei He, Wei He, Yanfang Li, Ke Zhang, Kensaku Mori, Zhengang Jiang

    Proceedings of SPIE 10950, Medical Imaging 2019     page: 1095025-1-11   2019.2

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  336. Spinal curvature segmentation and location by transfer learning

    Jiashi Zhao, Zhengang Jiang, Kensaku Mori, Liyuan Zhang, Wei He, Weili Shi, Yu Miao, Fei Yan, Fei He

    Proceedings of SPIE 10950, Medical Imaging 2019     page: 1095023-1-6   2019.2

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  337. Unsupervised segmentation of micro-CT images based on a hybrid of variational inference and adversarial learning

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

    Proceedings of SPIE 10953, Medical Imaging 2019     page: 109530L-1-8   2019.2

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  338. Weakly-supervised deep learning of interstitial lung disease types on CT images

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

    Proceedings of SPIE 10950, Medical Imaging 2019     page: 109501H-1-7   2019.2

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  339. 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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  340. Dynamic chest radiography for pulmonary function diagnosis: A validation study using 4D extended cardiac-torso (XCAT) phantom

    Rie Tanaka, Ehsan Samei, William Paul Segars, Ehsan Abadi, Holger Roth, Hirohisa Oda, Kensaku Mori

    Proceedings of SPIE 10948, Medical Imaging 2019     page: 109483I-1-7   2019.2

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  341. Polyp-size classification with RGB-D features for colonoscopy

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

    Proceedings of SPIE 10950, Medical Imaging 2019     page: 1095015-1-7   2019.2

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  342. Colonoscope tracking method based on shape estimation network

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

    Proceedings of SPIE 10951, Medical Imaging 2019     page: 109510Q-1-6   2019.2

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

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

    Proceedings of SPIE 10951, Medical Imaging 2019     page: 109510A-1-7   2019.2

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  344. 3Dプリンティングの最新動向

    森 健策

    インナービジョン 2019年2月号   Vol. 34 ( 2 ) page: 40-41   2019.2

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  345. 3Dプリンティングの最新動向

    森 健策

    インナービジョン 2019年2月号   Vol. 34 ( 2 ) page: 40-41   2019.2

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  346. Colonoscope tracking method based on shape estimation network

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

    Proceedings of SPIE 10951, Medical Imaging 2019     page: 109510Q-1-6   2019.2

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  347. Wavelength Dependence of Ultrahigh-Resolution Optical Coherence Tomography Using Supercontinuum for Biomedical Imaging Reviewed

    Norihiko Nishizawa, Hiroyuki Kawagoe, Masahito Yamanaka, Miyoko atsushima, Kensaku Mori, Tsutomu Kawabe

    IEEE Journal of Selected Topics in Quantum Electronics   Vol. 25 ( 1 ) page: 7101115   2019.1

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    DOI: 10.1109/JSTQE.2018.2854595

  348. AI支援手術に向けた鏡視下手術画像の自動認識システムの開発

    北口 大地, 松崎 博貴, 渡部 嘉気, 青柳 吉博, 佐藤 大介, 巣籠 悠輔, 原 聖吾, 森 健策, 伊藤 雅昭

    第1回日本メディカルAI学会学術集会, 日本メディカルAI学会誌   Vol. 1   page: 81   2019.1

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  349. 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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  350. MICCAI2018参加報告

    小田 昌宏, 大竹 義人, 伊東 隼人, 杉野 貴明, 斉藤 篤, 古川 亮, 大西 峻, 井宮 淳, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 118 ( 412 ) page: 221-228   2019.1

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  351. 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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  352. 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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  353. 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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  354. 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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  355. 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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  356. 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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  357. Automated hand eye calibration in laparoscope holding robot for robot assisted surgery

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

    IFMIA 2019     page: 0   2019.1

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  358. 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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  359. AI支援手術に向けた鏡視下手術画像の自動認識システムの開発

    北口 大地, 松崎 博貴, 渡部 嘉気, 青柳 吉博, 佐藤 大介, 巣籠 悠輔, 原 聖吾, 森 健策, 伊藤 雅昭

    第1回日本メディカルAI学会学術集会, 日本メディカルAI学会誌   Vol. 1   page: 81   2019.1

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  360. 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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  361. Regulatory Aspects on AI-based Medical Devices and Systems Reviewed

    CHINZEI Kiyoyuki, SHIMIZU Akinobu, MORI Kensaku, HARADA Kanako, TAKEDA Hideaki, HASHIZUME Makoto, ISHIZUKA Mayumi, KATO Nobumasa, KAWAMORI Ryuzo, KYO Shunei, NAGATA Kyosuke, YAMANE Takashi, SAKUMA Ichiro, OHE Kazuhiko, MITSUISHI Mamoru

    Regulatory Science of Medical Products   Vol. 9 ( 1 ) page: 31 - 36   2019

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    <p>Recent advances in artificial intelligence (AI) are propelling the development of AI-based medical and healthcare devices and systems. AI-based medical systems have new characteristics to be considered by developers and reviewers, namely, plasticity causing changes in system performance through learning, unpredictability of system behavior due to the black box nature of the AI process, and impact of advanced autonomy of AI-based medical systems on the relationship between patients and doctors. New research-and-development and medical-device-reviewing platforms need to be urgently discussed to prepare for up-coming new AI-based medical systems by considering aforementioned characteristics.</p>

    DOI: 10.14982/rsmp.9.31

    CiNii Research

  362. 大腸内視鏡診断への人工知能応用:Endocytoを用いた診断支援システムの研究開発経験から

    森 悠一, 工藤 進英, 森 健策

    日本消化器病学会雑誌   Vol. 115 ( 12 ) page: 1030-1036   2018.12

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  363. 大腸内視鏡治療誘導のためのRecurrent Neural Networkを用いた大腸内視鏡トラッキング手法の開発 Reviewed

    小田 昌宏, Holger R. Roth, 北坂 孝幸, 古川 和宏, 宮原 良二, 廣岡 芳樹, Nassir Navab, 森 健策

    日本バーチャルリアリティ学会論文誌   Vol. 23 ( 4 ) page: 249-252   2018.12

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    DOI: 10.18974/tvrsj.23.4_249

  364. 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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  365. Computer Assistance in Comparison of Kidney Function Variation Between Pre- and Post-nephrectomy

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

    RSNA2018     page: UR007-EB-WEA   2018.11

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  366. 3D High-Resolution Microstructure Imaging of the Heart

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

    RSNA2018     page: CA001-EC-X   2018.11

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  367. 病院内位置測位手法の検討

    山下 佳子, 大山 慎太郎, 大谷 智洋, 白鳥 義宗, 森 健策

    電子情報通信学会技術研究報告(MI), MICT2018-47   Vol. 118 ( 285 ) page: 41-44   2018.11

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  368. 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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  369. 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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  370. 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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  371. 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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  372. 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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  373. ステレオ手術顕微鏡画像からの脳表の 3 次元形状復元と術前 MRI 画像との融合による脳神経外科手術支援の検討

    林 雄一郎, 藤井 正純, 柴田 睦実, Dilip Bhandari, 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(Ⅷ)-4 ) page: 334-335   2018.11

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  374. 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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  375. 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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  376. 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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  377. 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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  378. 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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  379. 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

    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)-5 ) page: 248-249   2018.11

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  380. 超拡大内視鏡におけるAI

    森 健策, 伊東 隼人, 三澤 将史, 森 悠一, 工藤 進英

    日本光学会年次学術講演会講演予稿集     page: 226-227   2018.11

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

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

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  382. 3D High-Resolution Microstructure Imaging of the Heart

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

    RSNA2018     page: CA001-EC-X   2018.11

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  383. Computer Assistance in Comparison of Kidney Function Variation Between Pre- and Post-nephrectomy

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

    RSNA2018     page: UR007-EB-WEA   2018.11

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  384. 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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  385. DRINet for Medical Image Segmentation Reviewed

    Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert

    IEEE Transaction on Medical Imaging   Vol. 37 ( 11 ) page: 2453-2462   2018.10

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  386. 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     2018.9

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    DOI: 10.7326/M18-0249

  387. Fully Convolutional Network-based Eyeball Segmentation from Sparse Annotation for Eye Surgery Simulation Model

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

    International Workshop on Bio-Imaging and Visualization for Patient-Customized Simulations, BIVPCS 2018, LNCS 11042     page: 118-126   2018.9

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  388. 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     2018.9

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    DOI: 10.1016/j.gie.2018.09.024

  389. 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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  390. A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multiorgan Segmentation

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

    MICCAI 2018, LNCS 11073     page: 417-425   2018.9

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  391. BESNet: Boundary-enhanced Segmentation of Cells in Histopathological Images

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

    MICCAI 2018, LNCS 11071     page: 228-236   2018.9

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

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

    MICCAI 2018, LNCS 11071     page: 176-184   2018.9

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  393. Colon Shape Estimation Method for Colonoscope Tracking using Recurrent Neural Networks

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

    MICCAI 2018, LNCS 11073     page: 176-184   2018.9

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  394. A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multiorgan Segmentation

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

    MICCAI 2018, LNCS 11073     page: 417-425   2018.9

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  395. Anatomical location classification of gastroscopic images using DenseNet trained from Cyclical Learning Rate

    Qier Meng, Kiyohito Tanaka, Shin'ichi Satoh, Masaru Kitsuregawa, Yusuke Kurose, Tatsuya Harada, Hideaki Hayashi, Ryoma Bise, Seiichi Uchida, Masahiro Oda, Kensaku Mori

        page: PS1-51   2018.8

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  396. 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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  397. 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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  398. Radiomics nomogram for predicting the malignant potential of gastrointestinal stromal tumours preoperatively Reviewed

    Tao Chen, Zhenyuan Ning, Lili Xu, Xingyu Feng, Shuai Han, Holger R. Roth, Wei Xiong, Xixi Zhao, Yanfeng Hu, Hao Liu, Jiang Yu, Yu Zhang, Yong Li, Yikai Xu, Kensaku Mori, Guoxin Li

    European radiology     page: 1-9   2018.8

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    DOI: 10.1007/s00330-018-5629-2

  399. Anatomical location classification of gastroscopic images using DenseNet trained from Cyclical Learning Rate

    Qier Meng, Kiyohito Tanaka, Shin'ichi Satoh, Masaru Kitsuregawa, Yusuke Kurose, Tatsuya Harada, Hideaki Hayashi, Ryoma Bise, Seiichi Uchida, Masahiro Oda, Kensaku Mori

        page: PS1-51   2018.8

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  400. Attention U-Net: Learning Where to Look for the Pancreas

    Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh?, Nils Y. Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert

    Medical Imaging with Deep Learning MIDL2018     page: 00   2018.7

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  401. 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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  402. Fully convolutional networkを用いた少量画像データ学習からの頭部解剖構造抽出

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

    第37回日本医用画像工学会大会予稿集     page: OP1-1   2018.7

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  403. 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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  404. 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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  405. 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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  406. 腹腔鏡下手術のためのVR 手術再観察システムの開発

    鈴木 拓矢,道満 恵介,目加田 慶人,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: OP8-4   2018.7

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  407. 脳神経外科手術支援のための手術顕微鏡画像からの脳表の3次元形状復元に関する検討

    林 雄一郎, 柴田 睦実, 藤井 正純, 森 健策

    第37回日本医用画像工学会大会予稿集     page: OP8-1   2018.7

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  408. 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会大会予稿集     page: OP7-5   2018.7

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  409. 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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  410. 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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  411. 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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  412. 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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  413. Deformation matching of laparoscopic gastrectomy Navigation based on finite element analysis

    T. Chen, G. Wei, W. Shi, Y.Hu, J. Yu, Z.Jiang,K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s67-68   2018.6

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  414. Unsupervised deep learning based registration for aligning micro CT and histology images

    K. Nagara, S. Nakamura, H. Roth, M. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s155-157   2018.6

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  415. 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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  416. 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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  417. Deformation matching of laparoscopic gastrectomy Navigation based on finite element analysis

    T. Chen, G. Wei, W. Shi, Y.Hu, J. Yu, Z.Jiang, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s67-68   2018.6

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  418. 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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  419. Eye structure segmentation on micro-CT images using 3D fully convolutional network with sparsely-annotated training data

    T. Sugino, H. Roth, M. Oda, S. Omata, S. Sakuma, F. Arai, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s182-184   2018.6

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  420. 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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  421. Semi-supervised spherical K-means for segmenting idiopathic interstitial pneumonia from chest CT images

    C. Wang, T. Moriya, Y. Hayashi, M. Oda, H. Ohkubo, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s27-28   2018.6

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  422. 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, and Kensaku Mori

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

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  423. Abdominal artery segmentation from CT volumes using fully convolutional network for small artery segmentation

    Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori,

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s20-21   2018.6

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  424. Auto-context 3D fully convolutional networks for multi-scale semantic segmentation of abdominal CT volumes

    K. Mori, H. Roth, C. Shen, H. Oda, T. Sugino, M. Oda, Y. Hayashi, K. Misawa

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s18-19   2018.6

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  425. Unsupervised 3D micro-CT image segmentation based on a hybrid of VAE and GAN

    T. Moriya, H. Roth, S. Nakamura, H. Oda, K. Nagara, M. Oda, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s15-17   2018.6

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  426. Abdominal artery segmentation from CT volumes using fully convolutional network for small artery segmentation

    Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s20-21   2018.6

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  427. 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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  428. Auto-context 3D fully convolutional networks for multi-scale semantic segmentation of abdominal CT volumes

    K. Mori, H. Roth, C. Shen, H. Oda, T. Sugino, M. Oda, Y. Hayashi, K. Misawa

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s18-19   2018.6

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

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

    Gastroenterology   Vol. 154 ( 8 ) page: 2027-2029   2018.6

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    DOI: 10.1053/j.gastro.2018.04.003

  430. 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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    Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical structures (ranging from the large organs to thin vessels) can achieve competitive segmentation results, while avoiding the need for handcrafting features or training class-specific models. To this end, we propose a two-stage, coarse-to-fine approach that will first use a 3D FCN to roughly define a candidate region, which will then be used as input to a second 3D FCN. This reduces the number of voxels the second FCN has to classify to ∼10% and allows it to focus on more detailed segmentation of the organs and vessels. We utilize training and validation sets consisting of 331 clinical CT images and test our models on a completely unseen data collection acquired at a different hospital that includes 150 CT scans, targeting three anatomical organs (liver, spleen, and pancreas). In challenging organs such as the pancreas, our cascaded approach improves the mean Dice score from 68.5 to 82.2%, achieving the highest reported average score on this dataset. We compare with a 2D FCN method on a separate dataset of 240 CT scans with 18 classes and achieve a significantly higher performance in small organs and vessels. Furthermore, we explore fine-tuning our models to different datasets. Our experiments illustrate the promise and robustness of current 3D FCN based semantic segmentation of medical images, achieving state-of-the-art results.1

    DOI: 10.1016/j.compmedimag.2018.03.001

    Web of Science

    Scopus

    PubMed

  431. Port placement planning method for assistant surgeon in laparoscopic gastrectomy

    Y. Hayashi, K. Misawa, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s231-232   2018.6

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  432. 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

    Medical Imaging Technology   Vol. 36 ( 3 ) page: 127-132   2018.5

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  433. 特集/マイクロ解剖学のための微細解剖構造イメージング

    森 健策

    Medical Imaging Technology   Vol. 36 ( 3 ) page: 105-106   2018.5

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  434. DRINet for Medical Image Segmentation Reviewed

    Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert

    IEEE Transaction on Medical Imaging     2018.5

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    DOI: 10.1109/TMI.2018.2835303

  435. Regulatory Science on AI-based Medical Devices and Systems Reviewed

    Kiyoyuki Chinzei, Akinobu Shimizu, Kensaku Mori, Kanako Harada, Hideaki Takeda, Makoto Hashizume, Mayumi Ishizuka, Nobumasa Kato, Ryuzo Kawamori, Shunei Kyo, Kyosuke Nagata, Takashi Yamane, Ichiro Sakuma, Kazuhiko Ohe, Mamoru Mitsuishi

    Advanced Biomedical Engineering   Vol. 7   page: 118-123   2018.5

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    DOI: org/10.14326/abe.7.118

  436. Potential of artificial intelligence-assisted colonoscopy using an endocytoscope (with video) Reviewed

    Yuichi Mori, Shin-ei Kudo, Kensaku Mori

    Digestive Endoscopy   Vol. 30 ( S1 ) page: 52-53   2018.4

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    DOI: org/10.1111/den.13005

  437. Cascaded 3D Fully Convolutional Networks for Medical Image Segmentation

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

    GTC2018,     page: S8532   2018.3

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  438. Cascaded 3D Fully Convolutional Networks for Medical Image Segmentation

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

    GTC2018,     page: S8532   2018.3

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  439. MICCAI2017参加報告

    大竹義人, 伊藤康一, 小田昌宏, 備瀬竜馬, 諸岡健一, 周 向栄, 斉藤 篤, 清水昭伸, 増谷佳孝, 佐藤嘉伸, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 117 ( 518 ) page: 125-131   2018.3

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  440. 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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  441. 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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  442. 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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  443. 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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  444. 開腹手術映像における遮蔽物除去手法の改善 FFDによる位置合わせ精度の評価

    北坂孝幸, 奥田透生, 佐藤 準, 豊田誠仁, 澤野弘明, 末永康仁, 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: 31-32   2018.3

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  445. 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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  446. 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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  447. Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer. Reviewed International journal

    Katsuro Ichimasa, Shin-Ei Kudo, Yuichi Mori, Masashi Misawa, Shingo Matsudaira, Yuta Kouyama, Toshiyuki Baba, Eiji Hidaka, Kunihiko Wakamura, Takemasa Hayashi, Toyoki Kudo, Tomoyuki Ishigaki, Yusuke Yagawa, Hiroki Nakamura, Kenichi Takeda, Amyn Haji, Shigeharu Hamatani, Kensaku Mori, Fumio Ishida, Hideyuki Miyachi

    Endoscopy   Vol. 50 ( 3 ) page: 230 - 240   2018.3

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    BACKGROUND AND STUDY AIMS: Decisions concerning additional surgery after endoscopic resection of T1 colorectal cancer (CRC) are difficult because preoperative prediction of lymph node metastasis (LNM) is problematic. We investigated whether artificial intelligence can predict LNM presence, thus minimizing the need for additional surgery. PATIENTS AND METHODS: Data on 690 consecutive patients with T1 CRCs that were surgically resected in 2001 - 2016 were retrospectively analyzed. We divided patients into two groups according to date: data from 590 patients were used for machine learning for the artificial intelligence model, and the remaining 100 patients were included for model validation. The artificial intelligence model analyzed 45 clinicopathological factors and then predicted positivity or negativity for LNM. Operative specimens were used as the gold standard for the presence of LNM. The artificial intelligence model was validated by calculating the sensitivity, specificity, and accuracy for predicting LNM, and comparing these data with those of the American, European, and Japanese guidelines. RESULTS: Sensitivity was 100 % (95 % confidence interval [CI] 72 % to 100 %) in all models. Specificity of the artificial intelligence model and the American, European, and Japanese guidelines was 66 % (95 %CI 56 % to 76 %), 44 % (95 %CI 34 % to 55 %), 0 % (95 %CI 0 % to 3 %), and 0 % (95 %CI 0 % to 3 %), respectively; and accuracy was 69 % (95 %CI 59 % to 78 %), 49 % (95 %CI 39 % to 59 %), 9 % (95 %CI 4 % to 16 %), and 9 % (95 %CI 4 % - 16 %), respectively. The rates of unnecessary additional surgery attributable to misdiagnosing LNM-negative patients as having LNM were: 77 % (95 %CI 62 % to 89 %) for the artificial intelligence model, and 85 % (95 %CI 73 % to 93 %; P < 0.001), 91 % (95 %CI 84 % to 96 %; P < 0.001), and 91 % (95 %CI 84 % to 96 %; P < 0.001) for the American, European, and Japanese guidelines, respectively. CONCLUSIONS: Compared with current guidelines, artificial intelligence significantly reduced unnecessary additional surgery after endoscopic resection of T1 CRC without missing LNM positivity.

    DOI: 10.1055/s-0043-122385

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  448. Correction: Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer Reviewed

    Katsuro Ichimasa, Shin-ei Kudo, Yuichi Mori, Masashi Misawa, Shingo Matsudaira, Yuta Kouyama, Toshiyuki Baba, Eiji Hidaka, Kunihiko Wakamura, Takemasa Hayashi, Toyoki Kudo, Tomoyuki Ishigaki, Yusuke Yagawa, Hiroki Nakamura, Kenichi Takeda, Amyn Haji, Shigeharu Hamatani, Kensaku Mori, Fumio Ishida, Hideyuki Miyach

    Endoscopy   Vol. 50 ( 3 ) page: C2   2018.3

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    DOI: 10.1055/s-0044-100290

  449. Correction: Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer Reviewed

    Katsuro Ichimasa, Shin-ei Kudo, Yuichi Mori, Masashi Misawa, Shingo Matsudaira, Yuta Kouyama, Toshiyuki Baba, Eiji Hidaka, Kunihiko Wakamura, Takemasa Hayashi, Toyoki Kudo, Tomoyuki Ishigaki, Yusuke Yagawa, Hiroki Nakamura, Kenichi Takeda, Amyn Haji, Shigeharu Hamatani, Kensaku Mori, Fumio Ishida, Hideyuki Miyach

    Endoscopy   Vol. 50 ( 3 ) page: C2   2018.3

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  450. Correction: Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer Reviewed

    Katsuro Ichimasa, Shin-ei Kudo, Yuichi Mori, Masashi Misawa, Shingo Matsudaira, Yuta Kouyama, Toshiyuki Baba, Eiji Hidaka, Kunihiko Wakamura, Takemasa Hayashi, Toyoki Kudo, Tomoyuki Ishigaki, Yusuke Yagawa, Hiroki Nakamura, Kenichi Takeda, Amyn Haji, Shigeharu Hamatani, Kensaku Mori, Fumio Ishida, Hideyuki Miyach

    Endoscopy   Vol. 50 ( 3 ) page: C2   2018.3

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  451. 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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  452. Machine learning-based colon deformation estimation method for colonscope tracking

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

    Proc. SPIE 10576, Medical Imaging 2018     page: 1057619-1-1057619-6   2018.2

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

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

    Proc. SPIE 10575, Medical Imaging 2018     page: 1057502-1-1057502-6   2018.2

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    DOI: 10.1117/12.2287066

  454. Unsupervised pathology image segmantaion using representation learning with spherical k-means

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

    Proc. SPIE 10581, Medical Imaging 2018     page: 1058111-1-1058111-7   2018.2

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    DOI: 10.1117/12.2292172

  455. Unsupervised segmentation of 3D medical images based on clustering and deep representation learning

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

    Proc. SPIE 10578, Medical Imaging 2018     page: 105780-1-105780-7   2018.2

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    DOI: 10.1117/12.2293414

  456. Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional network

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

    Proc. SPIE 10574, Medical Imaging 2018     page: 105740B-1-105740B-6   2018.2

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    DOI: 10.1117/12.2293499

  457. Fine segmentation of tiny blood vessel based on fully-connected conditional random field

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

    Proc. SPIE 10574, Medical Imaging 2018     page: 10740K-1-10740K-7   2018.2

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    DOI: 10.1117/12.2293486

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

    Tao Chena, Guodong Wei, Weili Shic, Yuichiro Hayashi, Masahiro Oda, Zhengang Jiang, Guoxin Li, Kensaku Mori

    Proc. SPIE 10576, Medical Imaging 2018     page: 105761Y-1-10576Y-6   2018.2

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  459. 医用工学と放射線技術科学との融合:期待される新技術

    戸田 尚宏, 小林 哲生, 山谷 泰賀, 有村 秀孝, 内山 良一, 森 健策, 藤田 広志, 原 武史

    日本放射線技術学会雑誌, 第73回総会学術大会シンポジウム2   Vol. 74 ( 2 ) page: 175-190   2018.2

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  460. 術前術中後診断治療支援

    森 健策

    月刊「細胞]   Vol. 50 ( 1 ) page: 14-18   2018.1

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  461. 3Dプリンタの最新動向

    森 健策

    インナービジョン 2018年2月号   Vol. 33 ( 2 ) page: 35-36   2018.1

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  462. 3Dプリンタの最新動向

    森 健策

    インナービジョン 2018年2月号   Vol. 33 ( 2 ) page: 35-36   2018.1

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  463. Advanced Endoscopic Navigation: Surgical Big Data, Methodology, and Applications Reviewed

    Xiongbiao Luo, Kensaku Mori, Terry M. Peters

    Annual Review of Biomedical Engineering   Vol. 20 ( 1 ) page: 221 - 251   2018

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    Interventional endoscopy (e.g., bronchoscopy, colonoscopy, laparoscopy, cystoscopy) is a widely performed procedure that involves either diagnosis of suspicious lesions or guidance for minimally invasive surgery in a variety of organs within the body cavity. Endoscopy may also be used to guide the introduction of certain items (e.g., stents) into the body. Endoscopic navigation systems seek to integrate big data with multimodal information (e.g., computed tomography, magnetic resonance images, endoscopic video sequences, ultrasound images, external trackers) relative to the patient's anatomy, control the movement of medical endoscopes and surgical tools, and guide the surgeon's actions during endoscopic interventions. Nevertheless, it remains challenging to realize the next generation of context-aware navigated endoscopy. This review presents a broad survey of various aspects of endoscopic navigation, particularly with respect to the development of endoscopic navigation techniques. First, we investigate big data with multimodal information involved in endoscopic navigation. Next, we focus on numerous methodologies used for endoscopic navigation. We then review different endoscopic procedures in clinical applications. Finally, we discuss novel techniques and promising directions for the development of endoscopic navigation.

    DOI: 10.1146/annurev-bioeng-062117-120917

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

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

    Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 - 21st International Conference   Vol. 11073   page: 417 - 425   2018

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

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    Other Link: https://dblp.uni-trier.de/db/conf/miccai/miccai2018-4.html#RothSOSOHMM18

  465. [Implementation of artificial intelligence into colonoscopy: experience of research and development of computer-aided diagnostic system for endocytoscopy]. Reviewed

    Mori Y, Kudo SE, Mori K

    Nihon Shokakibyo Gakkai zasshi = The Japanese journal of gastro-enterology   Vol. 115 ( 12 ) page: 1030 - 1036   2018

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    DOI: 10.11405/nisshoshi.115.1030

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  466. 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     2017.12

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    DOI: 10.1111/ans.14331

  467. 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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  468. 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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  469. Machine Learning Techniques for Automated Accurate Organ Segmentation and Their Applications to Diagnosis Assistance

    Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori, Michitaka Fujiwara, Daniel Rueckert

    RSNA 2017 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 224   2017.11

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  470. 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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  471. 3D Microstructure Visualization of Lactiferous Duct Structure Based On Refraction X-Ray CT Imaging

    Kensaku Mori, Naoki Sunaguchi, Masami Ando, Tetsuya Yuasa, Daisuke Shimao, Shu Ichihara, Rajiv Gupta

    RSNA 2017 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 179   2017.11

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  472. 3Dプリンターの基礎と医療応用

    森 健策

    月刊心臓   Vol. 49 ( 11 ) page: 1104-1113   2017.11

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  473. 3Dプリンターの基礎と医療応用

    森 健策

    月刊心臓   Vol. 49 ( 11 ) page: 1104-1113   2017.11

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  474. 3D Microstructure Visualization of Lactiferous Duct Structure Based On Refraction X-Ray CT Imaging

    Kensaku Mori, Naoki Sunaguchi, Masami Ando, Tetsuya Yuasa, Daisuke Shimao, Shu Ichihara, Rajiv Gupta

    RSNA 2017 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 179   2017.11

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  475. 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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  476. Optimal port placement planning method for laparoscopic gastrectomy Reviewed

    Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 12 ( 10 ) page: 1677-1684   2017.10

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    DOI: 10.1007/s11548-017-1548-y

  477. Automatic Segmentation of Head Anatomical Structures from Sparsely-annotated Images Reviewed

    Takaaki Sugino, Holger R. Roth, Mohammad Eshghi, Masahiro Oda, Min Suk Chung, Kensaku Mori

    IEEE International Conference on Cyborg and Bionic Systems     page: 145-149   2017.10

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  478. 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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  479. 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

    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: 343-344   2017.10

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  480. 腹腔鏡下胃切除ナビゲーションにおける変形マッチングの有限要素法モデルを検証するための動物実験

    陳 韜, 魏 国棟,何 静怡,陳 光鋒,李 鐿,師 爲禮,祁 小龍,林 雄一郎,蒋 振剛,森 健策, 李 国新

    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: 339-340   2017.10

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  481. 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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  482. 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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  483. 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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  484. 腹腔鏡下手術の教育支援に向けた VR 訓練システムの開発

    鈴木拓矢,道満恵介,目加田慶人,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: 293   2017.10

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  485. 音声認識及びジェスチャ認識による腹腔鏡下手術ナビゲーション非接触操作システムの開発

    阿部史明,道満恵介,目加田慶人,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: 285   2017.10

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  486. 血管芯線を用いた経時リンパ節の自動対応付け

    舘 高基,小田昌宏,中村嘉彦,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: 278-279   2017.10

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  487. 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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  488. 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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  489. 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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  490. 開腹手術における 3 次元画像を用いた手術ナビゲーションシステムの臨床応用

    林 雄一郎, 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: 253-254   2017.10

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  491. 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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  492. MicroCT を用いた心筋配向解析手法の取り組み 〜MRI diffusion tensor 法との比較〜'

    秋田利明,小田紘久,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: 243   2017.10

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  493. 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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  494. 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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  495. 色ヒストグラム特徴を用いた腹腔鏡手術映像の体外・体内シーン分類

    山田 和希, 道満 恵介, 目加田 慶人, 三澤 一成, 森 健策

    平成 29 年度日本生体医工学会東海支部大会プログラム・抄録集     page: 00   2017.10

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  496. 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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  497. 畳み込みニューラルネットワークを利用した超拡大大腸内視鏡画像における腫瘍・非腫瘍の分類

    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 ( 220 ) page: 17-21   2017.9

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  498. Micro-CT Guided 3D Reconstruction of Histological images

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

    LNCS 10530     page: 93-101   2017.9

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  499. Motion Vector for Outlier Elimination in Feature Matching and Its Application in SLAM Based Laparoscopic Tracking

    Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Holger Roth, Kensaku Mori

    LNCS 10550     page: 60-69   2017.9

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  500. 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation

    Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken'ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori

    LNCS 10553     page: 222-230   2017.9

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  501. 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation

    Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken'ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori

    LNCS 10553     page: 222-230   2017.9

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  502. 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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  503. Tracking and Segmentation of the Airways in Chest CT Using a Fully Convolutional Network

    Qier Meng, Holger R. Roth, Takayuki Kitasaka, Masahiro Oda, Junji Ueno, Kensaku Mori

    LNCS 10434     page: 198-207   2017.9

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  504. TBS: Tensor-Based Supervoxels for Unfolding the Heart

    Hirohisa Oda, Holger R. Roth, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Julia A. Schnabel, Kensaku Mori

    LNCS 10433     page: 681-689   2017.9

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  505. 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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    Background and study aims Invasive cancer carries the risk of metastasis, and therefore, the ability to distinguish between invasive cancerous lesions and less-aggressive lesions is important. We evaluated a computer-aided diagnosis system that uses ultra-high (approximately x 400) magnification endocytoscopy (EC-CAD).
    Patients and methods We generated an image database from a consecutive series of 5843 endocytoscopy images of 375 lesions. For construction of a diagnostic algorithm, 5543 endocytoscopy images from 238 lesions were randomly extracted from the database for machine learning. We applied the obtained algorithm to 200 endocytoscopy images and calculated test characteristics for the diagnosis of invasive cancer. We defined a high-confidence diagnosis as having a &gt;= 90% probability of being correct.
    Results Of the 200 test images, 188 (94.0%) were assessable with the EC-CADsystem. Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were 89.4%, 98.9%, 94.1%, 98.8%, and 90.1 %, respectively. High-confidence diagnosis had a sensitivity, specificity, accuracy, PPV, and NPV of 98.1%, 100%, 99.3%, 100 %, and 98.8%, respectively.
    Conclusion: EC-CADmay be a useful tool in diagnosing invasive colorectal cancer.

    DOI: 10.1055/s-0043-105486

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  506. 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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  507. Multi-atlas pancreas segmentation: Atlas selection based on vessel structure Reviewed

    Kenichi 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

  508. 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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  509. 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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  510. 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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  511. 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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  512. 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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  513. 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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  514. A Study on Fine Blood Vessel Segmentation Using Fully-connected Conditional Random Field

        page: OP11-2   2017.7

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  515. 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予稿集     page: OP11-7   2017.7

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  516. 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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  517. 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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  518. A Study on Fine Blood Vessel Segmentation Using Fully-connected Conditional Random Field

        page: OP11-2   2017.7

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  519. 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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  520. 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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  521. 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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  522. Endocytoscope image classification using deep convolutional neural networks

    Masahiro Oda, Yutaka Hoshiyama, Masashi Misawa, Yuichi Mori, Kenichi Takeda, Sin-ei Kudo, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 12   page: S147-S148   2017.6

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  523. False positive reduction of abdominal artery segmentation from CT volumes based on deep convolutional neural networks

    Masahiro Oda, Tokunori Yamamoto, Yasushi Yoshino, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 12   page: S27-S29   2017.6

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  524. Automatic Anatomical Labeling of Arteries and Veins Using Conditional Random Fields

    Takayuki Kitasaka, Mitsuru Kagajo, Yukitaka Nimura, Yuichiro Hayashi, Masahiro Oda, Kazunari Misawa, Kensaku Mori

    8th International Conference on Information Processing in Computer-Assisted Interventions (IPCAI 2017)     page: -   2017.6

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  525. 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, Msahiro Oda, Kensaku Mori

    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY   Vol. 12 ( 5 ) page: 757 - 766   2017.6

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    Real-time characterization of colorectal lesions during colonoscopy is important for reducing medical costs, given that the need for a pathological diagnosis can be omitted if the accuracy of the diagnostic modality is sufficiently high. However, it is sometimes difficult for community-based gastroenterologists to achieve the required level of diagnostic accuracy. In this regard, we developed a computer-aided diagnosis (CAD) system based on endocytoscopy (EC) to evaluate cellular, glandular, and vessel structure atypia in vivo. The purpose of this study was to compare the diagnostic ability and efficacy of this CAD system with the performances of human expert and trainee endoscopists.
    We developed a CAD system based on EC with narrow-band imaging that allowed microvascular evaluation without dye (ECV-CAD). The CAD algorithm was programmed based on texture analysis and provided a two-class diagnosis of neoplastic or non-neoplastic, with probabilities. We validated the diagnostic ability of the ECV-CAD system using 173 randomly selected EC images (49 non-neoplasms, 124 neoplasms). The images were evaluated by the CAD and by four expert endoscopists and three trainees. The diagnostic accuracies for distinguishing between neoplasms and non-neoplasms were calculated.
    ECV-CAD had higher overall diagnostic accuracy than trainees (87.8 vs 63.4%; ), but similar to experts (87.8 vs 84.2%; ). With regard to high-confidence cases, the overall accuracy of ECV-CAD was also higher than trainees (93.5 vs 71.7%; ) and comparable to experts (93.5 vs 90.8%; ).
    ECV-CAD showed better diagnostic accuracy than trainee endoscopists and was comparable to that of experts. ECV-CAD could thus be a powerful decision-making tool for less-experienced endoscopists.

    DOI: 10.1007/s11548-017-1542-4

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  526. 機械学習を用いた内視鏡画像自動診断

    第56回 日本生体医工学会大会 プログラム・抄録集     page: 344   2017.5

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  527. 3Dプリンタの医療応用

    森 健策

    医用画像情報学会雑誌   Vol. 34 ( 1 ) page: 1-6   2017.4

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  528. 3Dプリンタの医療応用

    森 健策

    医用画像情報学会雑誌   Vol. 34 ( 1 ) page: 1-6   2017.4

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  529. Development of an automatic producing cholangiography procedure reconstructed from portal phase multidetector-row computed tomography images: Preliminary experience Reviewed

    Tomoaki Hirose, Tsuyoshi Igami, Kusuto Koga, Yuichiro Hayashi, Tomoki Ebata, Yukihiro, Yokoyama, Gen Sugawara, Takashi Mizuno, Junpei Yamaguchi, Kensaku Mori, Masato Nagino

    Surgery Today   Vol. 47 ( 3 ) page: 365-374   2017.3

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    DOI: 10.1007/s00595-016-1394-5

  530. Supervoxel classification forests for estimating pairwise image correspondences Reviewed

    Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker

    Pattern Recognition   Vol. 63   page: 561-569   2017.3

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    DOI: 10.1016/j.patcog.2016.09.026

  531. An improved method for pancreas segmentation using SLIC superpixels and interactive region merging

    Liyuan Zhang, Huamin Yang, Weili Shi, Yu Miao, Fei He, Wei He, Yanfang Li, Fei Yan, Huimao Zhang, Kensaku Mori, Zhengang Jiang

    Proceedings of SPIE   Vol. 10134   page: 101343H-1-101343H-12   2017.2

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    DOI: doi:10.1117/12.2254366

  532. Hessian-assisted supervoxel: structure-oriented voxel clustering and application to mediastinal lymph node detection from CT volumes

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

    Proceedings of SPIE   Vol. 10134   page: 101341D-1-101341D-12   2017.2

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    DOI: 10.1117/12.2254782

  533. Computer-aided diagnosis of mammographic masses using geometric verification-based image retrieval

    Qingliang Li, Weili SHI, Huamin Yang, Huimao Zhang, Tao CHEN, Kensaku Mori, Guoxin LI, Zhengang Jiang

    Proceedings of SPIE   Vol. 10134   page: 101342W-1-101342W-8   2017.2

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    DOI: doi:10.1117/12.2255799

  534. Extracellular matrix directions estimation of the heart on microfocus X-ray CT volumes

    Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

    Proceedings of SPIE   Vol. 10137   page: 101370M-1-101370M-9   2017.2

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    DOI: 10.1117/12.2254949

  535. Extraction of membrane structure in eyeball from MR volumes

    Masahiro Oda, Kin Taichi, Kensaku Mori

    Proceedings of SPIE   Vol. 10137   page: 101371S-1-101371S-6   2017.2

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    DOI: 10.1117/12.2254095

  536. A study on surgical field retrieval for intelligent laparotomy video archive system

    Takayuki Kitasaka, Yuki Kondo, Yuri Kimura, Yuki Takanashi, Hiroaki Sawano, Yasuhito Suenaga, Kazunari Misawa, and Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 327-328   2017.1

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  537. GPU Implementation of SLIC Supervoxel Oversegmentation

    Hirohisa Oda, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Julia A. Schnabel, and Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 266-268   2017.1

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  538. A study on surgical field retrieval for intelligent laparotomy video archive system

    Takayuki Kitasaka, Yuki Kondo, Yuri Kimura, Yuki Takanashi, Hiroaki Sawano, Yasuhito Suenaga, Kazunari Misawa, Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 327-328   2017.1

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  539. Airway segmentation from 3D chest CT volumes based on volume of interest using gradient vector flow

    Qier Meng, Takayuki Kitasaka, Masahiro Oda, and Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 192-195   2017.1

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  540. 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, and Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 54-56   2017.1

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  541. Airway segmentation from 3D chest CT volumes based on volume of interest using gradient vector flow

    Qier Meng, Takayuki Kitasaka, Masahiro Oda, Kensaku Mori

    International Forum on Medical Imaging in Asia (IFMIA)     page: 192-195   2017.1

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  542. 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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  543. 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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  544. 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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  545. 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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  546. 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

    電子情報通信学会技術研究報告(MI)   Vol. 116 ( 393 ) page: 185-190   2017.1

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  547. 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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    DOI: 10.1007/s11548-016-1456-6

  548. 3Dプリンタ・ユーザーインターフェイス等の最新動向

    森 健策

    インナービジョン 2017年2月号   Vol. 32 ( 2 ) page: 44-45   2017.1

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  549. 3Dプリンタ・ユーザーインターフェイス等の最新動向

    森 健策

    インナービジョン 2017年2月号   Vol. 32 ( 2 ) page: 44-45   2017.1

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  550. Airway extraction from 3D chest CT volumes based on iterative extension of VOI enhanced by cavity enhancement filter

    Qier Meng, Takayuki Kitasaka, Masahiro Oda, Kensaku Mori

    MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS   Vol. 10134   page: 101370M-1-101370M-9   2017

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    Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining an integrated 3-D airway tree structure from a CT volume is a quite challenging task. This paper presents a novel airway segmentation method based on intensity structure analysis and bronchi shape structure analysis in volume of interest (VOI). This method segments the bronchial regions by applying the cavity enhancement filter (CEF) to trace the bronchial tree structure from the trachea. It uses the CEF in each VOI to segment each branch and to predict the positions of VOIs which envelope the bronchial regions in next level. At the same time, a leakage detection is performed to avoid the leakage by analysing the pixel information and the shape information of airway candidate regions extracted in the VOI. Bronchial regions are finally obtained by unifying the extracted airway regions. The experiments results showed that the proposed method can extract most of the bronchial region in each VOI and led good results of the airway segmentation.

    DOI: 10.1117/12.2254233

    Web of Science

    Scopus

  551. かがくゼミナール「立体臓器モデルを作ろう」実施報告

    森 健策, 長柄 快, 舘 高基, 伊神 剛, 堀内 智子

    名古屋市科学館紀要     page: 35-41   2017

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  552. An improved method for pancreas segmentation using SLIC and interactive region merging

    Liyuan Zhang, Huamin Yang, Weili Shi, Yu Miao, Qingliang Li, Fei He, Wei He, Yanfang Li, Huimao Zhang, Kensaku Mori, Zhengang Jiang

    MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS   Vol. 10134   page: 101343H-1-101343H-12   2017

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    Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.

    DOI: 10.1117/12.2254366

    Web of Science

    Scopus

  553. Myofiber Visualization System for Micro CT Volumes of Left Ventricle

    Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

    RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 183   2016.12

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  554. Quantitative Analysis of Renal Dominant Regions based on Precise Renal Artery Segmentation'

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

    RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 214   2016.12

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  555. Naked Eye Visible Pores of Kohn and the Shapes of Alveoli on Magnified Three Dimensional Printed Model of the Lung Specimen by Virtual Image of Micro CT: Initial Experience

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

    RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 151   2016.11

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  556. Visualization Method of Myofiber Structure of the Left Ventricle Apex from Micro CT Volumes

    Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

    RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 94   2016.11

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  557. ステレオ内視鏡画像からの臓器形状復元手法における誤対応点削減処理の提案と手術画像への適用

    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25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 367-368   2016.11

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  558. 回帰木を用いたCT画像における臓器の局所化に関する特徴量の検討

    清水 南月, 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25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 365-366   2016.11

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  559. 脳神経外科手術ナビゲーションのためのステレオ画像からの脳表の3次元形状の復元

    Mohammad Eshghi, 林 雄一郎, 柴田 睦実, 小田 昌宏, 藤井 正純, 森 健策

    日本コンピュータ外科学会誌 第25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 246-247   2016.11

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  560. 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に関する初期的検討~統計的特徴量を利用したリンパ節検出率の改善~

    寶珠山 裕, Holger R.Roth, 小田 昌宏, 中村 嘉彦, 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25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 287-288   2016.11

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  561. 位置関係を用いた特徴量の導入による胆道領域セグメンテーション手法の改善

    陳 鵬飛, 田中 寛, 小田 紘久, 小田 昌宏, 林 雄一郎,伊神 剛, 椰野 正人, 森 健策

    日本コンピュータ外科学会誌 第25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 290-291   2016.11

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  562. 血管木構造構築手法の改善とその血管名称自動対応付けへの応用

    張 暁楠, 加賀城 充, 小田 昌宏, 林 雄一郎, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 293-294   2016.11

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  563. テンソルベースグラフカットを用いた血管抽出手法の実質臓器への応用

    王 成龍, 小田 昌宏, 吉野 能, 山本 徳則, 伊神 剛, 森 健策

    日本コンピュータ外科学会誌 第25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 295-296   2016.11

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  564. 腹腔鏡下胃切除術におけるポート位置決定支援のためのポート位置プランニングシステムの開発

    林 雄一郎, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 350-351   2016.11

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  565. 腹腔鏡ナビゲーションシステムにおける ORB-SLAM の適用に関する初期的検討

    王 成, Mohammad Eshghi, 小田 昌宏, 林 雄一郎, 三澤 一成, 蒋 振剛, 森 健策

    日本コンピュータ外科学会誌 第25回日本コンピュータ外科学会大会特集号(JSCAS2016)   Vol. 18 ( 4 ) page: 355-356   2016.11

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  566. From macro-scale to micro-scale computational anatomy: perspective of the next 20 years Reviewed

    Kensaku Mori

    Medical Image Analysis     2016.10

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    DOI: doi:10.1016/j.media.2016.06.034

  567. Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation

    Masahiro Oda, Natsuki Shimizu, Kenichi Karasawa, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, and Kensaku Mori

    MICCAI 2016   Vol. LNCS 9901   page: 556-563   2016.10

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  568. Tensor-Based Graph-Cut in Riemannian Metric Space and Its Application to Renal Artery Segmentation

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

    MICCAI 2016   Vol. LNCS 9902   page: 353-361   2016.10

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  569. 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 Surgery     page: (In Press)   2016.10

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    DOI: doi:10.1007/s11548-016-1492-2

  570. 特集 画像ナビゲーションによる消化器癌手術 各論:胃癌手術におけるナビゲーションの現状と新しい取り組み

    藤原 道隆, 三澤 一成, 森 健策, 川嶋 絋一郎, 田中 由浩, 小寺 泰弘

    手術   Vol. 70 ( 10 ) page: 1275-1286   2016.9

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  571. Supervoxel classification forests for estimating pairwise image correspondences Reviewed

    Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker

    Pattern Recognition   Vol. 63   page: 561–569   2016.9

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    DOI: DOI:10.1016/j.patcog.2016.09.026

  572. Cascade Registration of Micro CT Volumes taken in Multiple Resolutions

    Kai Nagara, Hirohisa Oda, Shota Nakamura, Masahiro Oda, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Daniel Rueckert, and Kensaku Mori

    Medical Imaging and Augmented Reality, 7th International Conference, MIAR 2016   Vol. LNCS 9805   page: 269–280   2016.8

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  573. Development of an automatic producing cholangiography procedure reconstructed from portal phase multidetectorrow computed tomography images: Preliminary experience Reviewed

    Tomoaki Hirose, Tsuyoshi Igami, Kusuto Koga, Yuichiro Hayashi, Tomoki Ebata, Yukihiro, Yokoyama, Gen Sugawara, Takashi Mizuno, Junpei Yamaguchi, Kensaku Mori, Masato Nagino

    Surgery Today     2016.8

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    DOI: DOI: 10.1007/s00595-016-1394-5

  574. 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 2016   Vol. 48 ( 12 ) page: 1110-1118   2016.8

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    DOI: 10.1055/s-0042-113609

  575. Ⅰ 医療分野における3Dプリンタ利活用の最新動向 医療分野における3Dプリンタの応用動向─診療報酬改定の影響と今後の動向も含めて

    森 健策

    インナービジョン 2016年7月号   Vol. 31 ( 7 ) page: 4-7   2016.7

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  576. Ⅲ 3Dプリンティングのハンドリングのノウハウ

    森 健策

    インナービジョン 2016年7月号   Vol. 31 ( 7 ) page: 20-24   2016.7

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  577. 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     page: (accepted)   2016.7

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    DOI: DOI: 10.1007/s11548-016-1456-6

  578. 開腹手術映像の知的アーカイブのための遮蔽物除去手法の評価

    北坂 孝幸, 後藤 慎史, 杉田 峻, 富永 迅, 澤野 弘明, 末永 康仁, 三澤一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 116 ( 160 ) page: 5-6   2016.7

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  579. 3次元腹部X線CT像からの経時リンパ節の自動検出精度の検討

    中村 嘉彦, 寳珠山 裕, 林 雄一郎, 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. 116 ( 160 ) page: 39-42   2016.7

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  580. A Study on Fast Interactive Segmentation on 3D Medical Image using Graph-cut

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

      Vol. 116 ( 160 ) page: 23-28   2016.7

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  581. 腹腔鏡下手術ナビゲーションシステムのため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. 116 ( 160 ) page: 7-12   2016.7

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  582. Surgical field retrieval for intelligent laparotomy video archive system

    Takayuki Kitasaka, Shinji Goto, Shun Sugita, Hayate Tominaga, Hiroaki Sawano, Yasuhito Suenaga, Kazunari Misawa, Kensaku MORI

        page: PP-7   2016.7

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  583. 腹腔鏡下胃切除術のための手術ナビゲーションシステムにおけるステレオ内視鏡画像からの臓器形状復元に関する検討

    柴田 睦実, 森田 千尋, 林 雄一郎, 小田 昌宏, 三澤 一成, 森 健策

    第35回日本医用画像工学会大会予稿集     page: OP1-10   2016.7

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  584. 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に関する初期的検討

    寳珠山 裕, 二村 幸孝, 小田 昌宏, 三澤 一成, 藤原 道隆, 森 健策

    第35回日本医用画像工学会大会予稿集     page: OP7-4   2016.7

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  585. Regression Forest を用いた膵臓領域の局所化に関する初期的検討

    清水 南月, 小田 昌宏, 三澤 一成 ,藤原 道隆, 森 健策

    第35回日本医用画像工学会大会予稿集     page: OP8-7   2016.7

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  586. 腹腔鏡下手術ナビゲーションシステムにおける剛体と非剛体レジストレーションを用いた臓器表面形状による位置合わせ手法の検討

    林 雄一郎, 森田 千尋, 三澤 一成, 森 健策

    第35回日本医用画像工学会大会予稿集     page: PP-29   2016.7

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  587. Reduction of User Interaction Cost of Graph-cut Using Gradient Vector Flow in Blood Vessel Segmentation

    Chenglong WANG, Masahiro ODA, Yasushi YOSHINO, Tokunori YAMAMOTO, Kensaku MORI

        page: OP6-5   2016.7

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  588. Myofiber Extraction from Micro CT Volumes by Combining Structure Tensor and Hessian Matrix

    Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

        page: OP6-6   2016.7

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  589. Extraction of Intrahepatic Bile Duct from Dual-energy CT Volumes by Selective Use of Feature Values from Different Scales

    Pengfei CHEN, Hiroshi TANAKA, Masahiro ODA, Yuichiro HAYASHI, Tsuyoshi IGAMI, Masato NAGINO, Kensaku MORI

        page: OP9-1   2016.7

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  590. A Study on Volume Similarity Metric for Clinical and Micro CT Volume Registration

    NAGARA, Shota NAKAMURA, Masahiro ODA, Hirotoshi HOMMA, Hirotsugu TAKABATAKE, Masaki MORI, Hiroshi NATORI, Kensaku MORI

        page: OP9-2   2016.7

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  591. A Study on Volume Similarity Metric for Clinical and Micro CT Volume Registration

    NAGARA, Shota NAKAMURA, Masahiro ODA, Hirotoshi HOMMA, Hirotsugu TAKABATAKE, Masaki MORI, Hiroshi NATORI, Kensaku MORI

        page: OP9-2   2016.7

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  592. A Study on Fast Interactive Segmentation on 3D Medical Image using Graph-cut

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

      Vol. 116 ( 160 ) page: 23-28   2016.7

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  593. 3次元腹部X線CT像からの経時リンパ節の自動検出精度の検討

    中村 嘉彦, 寳珠山 裕, 林 雄一郎, 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. 116 ( 160 ) page: 39-42   2016.7

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  594. Port placement planning method for assistant surgeon in laparoscopic gastrectomy

    Y. Hayashi, K. Misawa, K. Mori

    International Journal of Computer Assisted Radiology and Surgery   Vol. 13 ( 1 ) page: s231-232   2016.6

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  595. Characterization of Colorectal Lesions Using a Computer-Aided Diagnostic System for Narrow-Band Imaging Endocytoscopy Reviewed

    Masashi Misawa, Shin-ei Kudo, Yuichi Mori, Hiroki Nakamura, Shinichi Kataoka, Yasuharu Maeda, Toyoki Kudo, Takemasa Hayashi, Kunihiko Wakamura, Hideyuki Miyachi, Atsushi Katagiri, Toshiyuki Baba, Fumio Ishida, Haruhiro Inoue, Yukitaka Nimura, Kensaku Mori

    Gastroenterology   Vol. 150 ( 7 ) page: 1531-1532.e3   2016.6

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    DOI: DOI:10.1053/j.gastro.2016.04.004

  596. Port placement planning assistance for laparo - scopic gastrectomy based on anatomical structure analysis

    Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S265-S266   2016.6

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  597. Comparison of Hessian-Matrix- and structure-tensor-based methods for myofiber structure extraction from micro-CT volumes

    Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S38-S39   2016.6

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  598. Evaluation of efficiency of feature values for false positive reduction of automated mediastinal lymph node detection

    Chenglong Wang, Mitsuru Kagajo, Yoshihiko Nakamura, Masahiro Oda, Yasushi Yoshino, Tokunori Yamamoto, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S42-S43   2016.6

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  599. Segmentation method of abdominal arteries from CT volumes utilizing intensity transition along arteries

    Masahiro Oda, Tokunori Yamamoto, Yasushi Yoshino, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S46-S47   2016.6

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  600. Evaluation of efficiency of feature values for false positive reduction of automated mediastinal lymph node detection

    Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S130-S131   2016.6

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  601. A multi-scale and multi-modality statistical model of pancreas

    Akinobu Shimizu, Hidekata Hontani, Naoki Kobayashi, Hayaru Shouno, Kensaku Mori, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S165-S166   2016.6

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  602. Scale-seamless registration and visualization for micro-computational anatomy

    Kensaku Mori, Kai Nagara, Shota Nakamura, Masahiro Oda

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S169-S171   2016.6

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  603. An improved method for intrahepatic bile duct extraction from dual-energy CT volumes based on sample data adjustment for SVM training

    Pengfei Chen, Hiroshi Tanaka, Masahiro Oda, Yukihiro Hayashi, Tsuyoshi Igami, Masato Nagino, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S218-S219   2016.6

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  604. An improved method for intrahepatic bile duct extraction from dual-energy CT volumes based on sample data adjustment for SVM training

    Pengfei Chen, Hiroshi Tanaka, Masahiro Oda, Yukihiro Hayashi, Tsuyoshi Igami, Masato Nagino, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S218-S219   2016.6

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  605. A multi-scale and multi-modality statistical model of pancreas

    Akinobu Shimizu, Hidekata Hontani, Naoki Kobayashi, Hayaru Shouno, Kensaku Mori, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume

    International Journal of Computer Assisted Radiology and Surgery 2016   Vol. 11 ( 1 ) page: S165-S166   2016.6

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  606. Progressive internal landmark registration for surgical navigation in laparoscopic gastrectomy for gastric cancer Reviewed

    Yuichiro Hayashi, Kazunari Misawa, David J. Hawkes, Kensaku Mor

    International Journal of Computer Assisted Radiology Surgery   Vol. 11 ( 5 ) page: 837-845   2016.5

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    DOI: doi: 10.1007/s11548-015-1346-3

  607. Clinical application of a surgical navigation system based on virtual laparoscopy in laparoscopic gastrectomy for gastric cancer Reviewed

    Yuichiro Hayashi, Kazunari Misawa, Masahiro Oda, David J. Hawkes, Kensaku Mori

    International Journal of Computer Assisted Radiology Surgery   Vol. 11 ( 5 ) page: 827-836   2016.5

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    DOI: doi: 10.1007/s11548-015-1293-z

  608. A Computer-Aided Diagnosis System for Endocytoscopy With Narrow-Band Imaging Provides Highly Accurate Diagnosis Reviewed

    Misawa Masashi, Kudo Shin-ei, Mori Yuichi, Kataoka Shinichi, Maeda Yasuharu, Sako Tomoya, Watanabe Mayuko, Kudo Toyoki, Hisayuki Tomokazu, Wakamura Kunihiko, Hayashi Takemasa, Miyachi Hideyuki, Katagiri Atsushi, Ishida Fumio, Inoue Haruhiro, Nimura Yukitaka, Mori Kensaku

    GASTROINTESTINAL ENDOSCOPY   Vol. 83 ( 5 ) page: AB287 - AB288   2016.5

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    DOI: 10.1016/j.gie.2016.03.449

    Web of Science

  609. X線CTやMRIにおける3D画像

    森 健策

    メディカル&イメージング MOOK   Vol. 4   page: 57-64   2016.4

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  610. 多元計算解剖モデルの体系的開発 Sytematic Development of Multidisciplinary Computational Anatomy Models 腫瘍マルチスケール時空間モデリング

    森 健策

    第55回 日本生体医工学会大会プログラム・抄録集   Vol. 54 ( 1 ) page: 97   2016.4

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  611. Precise renal artery segmentation for estimation of renal vascular dominant regions

    Chenglong Wang, Mitsuru Kagajo, Yoshihiko Nakamura, Masahiro Oda, Yasushi Yoshino, Tokunori Yamamoto, and Kensaku Mori

    Proceedings of SPIE Medical Imaging 2016   Vol. 9784   2016.3

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    DOI: 10.1117/12.2217492

  612. Intensity targeted radial structure tensor analysis and its application for automated mediastinal lymph node detection from CT volumes

    Hirohisa Oda, Yukitaka Nimura, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, and Kensaku Mori

    Proceedings of SPIE Medical Imaging 2016   Vol. 9785   2016.3

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    DOI: 10.1117/12.2216663

  613. Ensemble lymph node detection from CT volumes combining local intensity structure analysis approach and appearance learning approach

    Yoshihiko Nakamura, Yukitaka Nimura, Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Hidemi Goto, Michitaka Fujiwara, Kazunari Misawa, and Kensaku Mori

    Proceedings of SPIE Medical Imaging 2016   Vol. 9785   2016.3

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    DOI: 10.1117/12.2214925

  614. Position-based adjustment of landmark based correspondence finding in electromagnetic sensor-based colonoscope tracking method

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

    Proceedings of SPIE Medical Imaging 2016   Vol. 9786   2016.3

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    DOI: 10.1117/12.2216371

  615. 管腔構造に対する自動解剖名称アノテーション

    森 健策

    121回日本解剖学会総会・全国学術集会 講演プログラム・抄録集     page: 93   2016.3

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  616. 腹部動脈の血管名自動対応付けにおける分岐パターンを考慮した機械学習の利用の検討

    張 暁楠, 加賀城 充, 小田 昌宏, 三澤 一成, 森 健策

    電子情報通信学会 2016年総合大会プログラム   Vol. D-16-11   page: 81   2016.3

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  617. 医療分野における3Dプリンタの応用

    森 健策

    宙舞   ( 78 ) page: 2-6   2016.2

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  618. エキスパートによるRSNA 2015ベストリポート : 3Dプリンタ,ユーザーインターフェイス等の動向を中心に

    森 健策

    インナービジョン 2016年2月号   Vol. 31 ( 2 ) page: 41-42   2016.2

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  619. 気管支構造情報を用いた気管支内腔壁面への気管支枝名自動表示の精度向上

    山本 貴洋, 北坂 孝幸, 二村 幸孝, 末永 康仁, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 401 ) page: 13-18   2016.1

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  620. 条件付き確率場を利用した腹部動脈および肝門脈系の血管名自動対応付け

    加賀城 充, 二村 幸孝, 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. 115 ( 401 ) page: 19-24   2016.1

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  621. マルチスケール画像処理のためのマイクロCT画像データベース構築 多元計算解剖学における画像処理アルゴリズム開発のためのデータベース構築

    森 健策, 長柄 快, 小田 昌宏

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 401 ) page: 165-170   2016.1

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  622. MICCAI2015参加報告

    花岡 昇平, 唐澤 健一. 本谷 秀堅. 周 向栄. 平野 靖, 小田 昌宏, 増谷 佳孝, 清水 昭伸, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 401 ) page: 177-182   2016.1

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  623. Dual-energy CT画像からの特徴抽出に基づく肝内胆管領域自動抽出

    陳 鵬飛, 田中 寛, 小田 昌宏, 林 雄一郎, 伊神 剛, 梛野 正人, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 401 ) page: 187-192   2016.1

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  624. 解剖学的ランドマークに基づく自動臓器局所化とその膵臓セグメンテーションへの応用

    唐澤 健一, 小田 昌宏, 北坂 孝幸, 花岡 昇平, 林 雄一郎, 二村 幸孝, 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. 115 ( 401 ) page: 215-220   2016.1

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  625. スケールシームレスナビゲーションのためのマルチスケールレジストレーション法の開発 マイクロCT像を用いた基礎的検討

    長柄 快, 中村 彰太, 小田 昌宏, 北坂 孝幸, 本間 裕敏, 高畠 博嗣, 森 雅樹, 名取 博, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 401 ) page: 351-356   2016.1

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  626. 腹腔鏡下手術ナビゲーションシステムにおける臓器表面形状を用いた術中の非剛体レジストレーションに関する検討

    森田 千尋, 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. 115 ( 401 ) page: 357-362   2016.1

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  627. Accurate Airway Segmentation Based on Intensity Structure Analysis and Graph-cut

    Qier Meng, Takayuki Kitasaka, Yukitaka Nimura, Masahiro Oda, Kensaku Mori

    MEDICAL IMAGING 2016: IMAGE PROCESSING   Vol. 9784   2016

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    This paper presents a novel airway segmentation method based on intensity structure analysis and graph-cut. Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3-D airway tree structure from a CT volume is quite challenging. Several researchers have proposed automated algorithms basically based on region growing and machine learning techniques. However these methods failed to detect the peripheral bronchi branches. They caused a large amount of leakage. This paper presents a novel approach that permits more accurate extraction of complex bronchial airway region. Our method are composed of three steps. First, the Hessian analysis is utilized for enhancing the line-like structure in CT volumes, then a multiscale cavity-enhancement filter is employed to detect the cavity-like structure from the previous enhanced result. In the second step, we utilize the support vector machine (SVM) to construct a classifier for removing the FP regions generated. Finally, the graph-cut algorithm is utilized to connect all of the candidate voxels to form an integrated airway tree. We applied this method to sixteen cases of 3D chest CT volumes. The results showed that the branch detection rate of this method can reach about 77.7% without leaking into the hng parenchyma areas.

    DOI: 10.1117/12.2216670

    Web of Science

    Scopus

  628. An Improved Robust Hand-Eye Calibration for Endoscopy Navigation System

    Wei He, Kumsok Kang, Yanfang Li, Weili Shi, Yu Miao, Fei He, Fei Yan, Huamin Yang, Huimao Zhang, Kensaku Mori, Zhengang Jiang

    MEDICAL IMAGING 2016: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING   Vol. 9786   2016

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    Endoscopy is widely used in clinical application, and surgical navigation system is an extremely important way to enhance the safety of endoscopy. The key to improve the accuracy of the navigation system is to solve the positional relationship between camera and tracking marker precisely. The problem can be solved by the hand eye calibration method based on dual quaternions. However, because of the tracking error and the limited motion of the endoscope, the sample motions may contain some incomplete motion samples. Those motions will cause the algorithm unstable and inaccurate. An advanced selection rule for sample motions is proposed in this paper to improve the stability and accuracy of the methods based on dual quaternion. By setting the motion filter to filter out the incomplete motion samples, finally, high precision and robust result is achieved. The experimental results show that the accuracy and stability of camera registration have been effectively improved by selecting sample motion data automatically.

    DOI: 10.1117/12.2216910

    Web of Science

    Scopus

  629. Surgical and Radiological Studies on the Length of the Hepatic Ducts Reviewed

    Tomoaki Hirose, Tsuyoshi Igami, Tomoki Ebata, Yukihiro Yokoyama, Gen Sugawara, Takashi Mizuno, Kensaku Mori, Masahiko Ando, Masato Nagino

    World Journal of Surgery   Vol. 39 ( 12 )   2015.12

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    DOI: doi: 10.1007/s00268-015-3201-7

  630. 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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    DOI: 10.1117/1.JMI.2.4.044004

  631. New Tools for Analysis of Peripheral Lung Structures by Virtual Microscopy and Three Dimensional Printed out Scale up Tangible Model for Realization by Micro Focused CT Data of the Lung Specimen

    Hiroshi Natori, Hirotsugu Takabatake, Kensaku Mori, Masahiro Oda, Masaki Mori, Hirotoshi Homma, and Hiroyuki Koba

    RSNA 2015 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF     page: 278   2015.12

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  632. A Study on Improvement of Airway Segmentation using Hybrid Method

    Qier Meng, Takayuki Kitasaka, Yukitaka Nimura, Masahiro Oda, and Kensaku Mori

    The 3rd IAPR Asian Conference on Pattern Recognition (ACPR2015)     page: 225-229   2015.11

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  633. 超拡大内視鏡画像におけるテクスチャ情報を利用した自動病理診断に関する予備的検討

    二村 幸孝, 森 悠一, 三澤 将史, 工藤 進英, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 264-265   2015.11

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  634. 縦隔リンパ節検出のためのRadial Structure Tensor解析の改良に関する基礎的検討

    小田 紘久, 二村 幸孝, 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, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 256-257   2015.11

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  635. 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

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 254-255   2015.11

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  636. 音声操作手術ナビゲーションシステムのための血管観察視点位置の自動決定法に関る検討

    林 雅大, 堂満 恵介, 目加田 慶人, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 252-253   2015.11

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  637. 深層学習を用いた3次元腹部CT像からのリンパ節検出における過検出削減に関する検討-学習データの人工生成が過検出削減に与える影響-

    寳珠山 裕, 二村 幸孝, 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24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 244-245   2015.11

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  638. 3次元腹部CT像からのリンパ節抽出における特徴量計算のための球状モデルの利用

    孟 晨, 二村 幸孝, 小田 昌宏, 北坂 孝幸, 中村 嘉彦, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 242-243   2015.11

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  639. Graph-cutと血管追跡法を併用した腎動脈精密抽出手法における血管抽出性能評価

    王 成龍, 加賀城 充, 中村 嘉彦, 小田 昌宏, 吉野 能, 山本 徳則, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 208-209   2015.11

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  640. マルチスケール空洞強調フィルタと機械学習を用いた頑健性の高い気道抽出

    蒙 琪儿, 小田 紘久, 北坂 孝幸, 二村 幸孝, 小田 昌宏, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 206-207   2015.11

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  641. 条件付き確率場を用いた腹部動脈の血管名自動対応付け

    加賀城 充, 小田 昌宏, 林 雄一郎, 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24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 202-203   2015.11

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  642. 3次元画像を用いた開腹手術の手術ナビゲーションシステムにおける手術支援画像の提示法の検討

    林 雄一郎, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 170-171   2015.11

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  643. 腹腔鏡手術ナビゲーションシステムのための軟性鏡カメラ方向測定装置の開発

    長柄 快, 柴田 睦実, 清水 南月, 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24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 166-167   2015.11

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  644. 腹腔鏡下手術ナビゲーションにおける非剛体レジストレーションを利用した術中の位置合わせに関する検討

    森田 千尋, 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24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 163-164   2015.11

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  645. 多元計算解剖学とコンピュータ外科-高度知能化治療支援に向けて-

    森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 156   2015.11

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  646. マイクロCT画像からの線維方向追跡に関する検討

    小田 紘久, 小田 昌宏, 北坂 孝幸, 秋田 利明, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 301 ) page: 9-14   2015.11

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  647. A Study on Improvement of Airway Segmentation using Hybrid Method

    Qier Meng, Takayuki Kitasaka, Yukitaka Nimura, Masahiro Oda, Kensaku Mori

    The 3rd IAPR Asian Conference on Pattern Recognition (ACPR2015)     page: 225-229   2015.11

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  648. 3次元腹部CT像からのリンパ節抽出における特徴量計算のための球状モデルの利用

    孟 晨, 二村 幸孝, 小田 昌宏, 北坂 孝幸, 中村 嘉彦, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 242-243   2015.11

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  649. 3次元画像を用いた開腹手術の手術ナビゲーションシステムにおける手術支援画像の提示法の検討

    林 雄一郎, 三澤 一成, 森 健策

    日本コンピュータ外科学会誌 第24回日本コンピュータ外科学会大会特集号   Vol. 17 ( 3 ) page: 170-171   2015.11

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  650. Clinical application of a surgical navigation system based on virtual laparoscopy in laparoscopic gastrectomy for gastric cancer Reviewed

    Yuichiro Hayashi , Kazunari Misawa, Masahiro Oda, David J Hawkes, Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery     2015.10

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    DOI: doi: 10.1007/s11548-015-1293-z

  651. Leap Motionによる外科手術ナビゲーションシステム操作の一提案

    佐藤 淳史, 道満 恵介, 目加田 慶人, 三澤 一成, 森 健策

    平成27年度日本生体医工学会東海支部大会プログラム・抄録集     page: 18   2015.10

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  652. Tracking Accuracy Evaluation of Electromagnetic Sensor-based Colonoscope Tracking Method

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

    Second International Workshop on Computer-Assisted and Robotic Endoscopy Held in Conjunction with MICCAI 2015   Vol. LNCS 9515   page: 101-108   2015.10

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  653. Supervoxel Classification Forests for Estimating Pairwise Image Correspondences Machine Learning in Medical Imaging

    Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, and Ben Glocker

    MICCAI 2015   Vol. LNCS 9352   page: 94-101   2015.10

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  654. Structure specific atlas generation and its application to pancreas segmentation from contrasted abdominal CT volumes

    Kenichi Karasawa, Masahiro Oda, Kensaku Mori, and Takayuki Kitasaka

    MICCAI 2015 Workshop on Medical Computer Vision     page: Algorithms for Big Data   2015.10

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  655. 特集/マルチモダリティ医用画像の統合解析: マルチモダリティ画像の融合―治療応用を目的とした CT/超音波/内視鏡画像融合―

    森 健策

    Medical Imaging Technology   Vol. 33 ( 4 ) page: 170-176   2015.9

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  656. `Observation-driven adaptive differential evolution and its application to accurate and smooth bronchoscope three-dimensional motion tracking Reviewed

    Xiongbiao Luo, Ying Wan, Xiangjian He, and Kensaku Mori

    Medical Image Analysis   Vol. 24(1)   page: 282-296   2015.8

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

    DOI: doi:10.1016/j.media.2015.01.002

  657. Radial Structure Tensor に基づく塊状構造強調フィルタの縦隔リンパ節検出への利用に関する検討

    小田 紘久, 二村 幸孝, 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, 森 健策

    第18回画像の認識・理解シンポジウム(MIRU2015)     page: SS4-10   2015.7

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  658. 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

    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予稿集     page: PP34   2015.7

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  659. 臓器情報に基づくルールベースの後処理による腹部動脈に対する解剖学的名称の自動対応付け精度向上

    加賀城 充, 中村 嘉彦, 林 雄一郎, 小田 昌宏, 北坂 孝幸, 三澤 一成, 森 健策

    第34回日本医用画像工学会大会予稿集     page: PP31   2015.7

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  660. A preliminary study on false positive reduction of bronchus segmentation using SVM

    Qier Meng, Takayuki Kitasaka, Hirohisa Oda, Yukitaka Nimura, Yoshihiko Nakamura, Masahiro Oda, Kensaku Mori

        page: PP30   2015.7

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  661. 気管支構造情報を利用した気管支内腔壁面への気管支枝名表示の自動化手法の開発

    山本 貴洋, 北坂 孝幸, 二村 幸孝, 末永 康仁, 森 健策

    第34回日本医用画像工学会大会予稿集     page: PP29   2015.7

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  662. 腹腔鏡下手術ナビゲーションシステムにおける臓器と血管の情報に基づく位置合わせ手法の検討

    林 雄一郎, 森田 千尋, 三澤 一成, 森 健策

    第34回日本医用画像工学会大会予稿集     page: PP28   2015.7

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  663. 大腸病変の超拡大血管所見に対する自動診断システム

    三澤 将史, 工藤 進英, 森 悠一, 片岡 伸一, 中村 大樹, 工藤 豊樹, 林 武雅, 若村 邦彦, 宮地 英行, 片桐 敦, 石田 文生, 井上 晴洋, 二村 幸孝, 森 健策

    第34回日本医用画像工学会大会予稿集     page: PP21   2015.7

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  664. 球状モデルを用いた腹部CT像からのリンパ節自動検出手法の検討

    孟 晨, 小田 紘久, 二村 幸孝, 小田 昌宏, 北坂 孝幸, 中村 嘉彦, 三澤 一成, 森 健策

    第34回日本医用画像工学会大会予稿集     page: PP19   2015.7

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  665. 3次元腹部造影CT像からの膵臓セグメンテーションにおける線状構造情報を用いた患者固有アトラス選択の有効性に関する検討

    唐澤 健一, 小田 昌宏, 林 雄一郎, 二村 幸孝, 北坂 孝幸, 三澤 一成, 藤原 道隆, 森 健策

    第34回日本医用画像工学会大会予稿集     page: OP8-4   2015.7

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  666. 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

    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予稿集     page: OP6-4   2015.7

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  667. SURF特徴量の照合による腹腔鏡手術映像へのタグ付け

    水谷 友一, 佐藤 梨果, 道満 恵介, 目加田 慶人, 三澤 一成, 森 建策

    第34回日本医用画像工学会大会予稿集     page: OP4-3   2015.7

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  668. 開腹手術映像における遮蔽物除去手法の高精度化

    北坂 孝幸, 池井 友啓, 林 祐斗, 八重嶋 秀, 澤野 弘明, 水野 慎士, 末永 康仁, 三澤 一成

    第34回日本医用画像工学会大会予稿集     page: OP4-2   2015.7

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  669. 深層学習を用いたCT像からのリンパ節検出における過検出削減に関する検討

    寳珠山 裕, 二村 幸孝, 小田 昌宏, 三澤 一成, 藤原 道隆, 森 健策

    第34回日本医用画像工学会大会予稿集     page: OP1-4   2015.7

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  670. 複数検出手法の統合による3次元腹部X線CT像からの腹部リンパ節検出手法の精度向上

    中村 嘉彦, 二村 幸孝, 小田 昌宏, 北坂 孝幸, 古川 和宏, 後藤 秀実, 藤原 道隆, 三澤 一成, 森 健策

    第34回日本医用画像工学会大会予稿集     page: OP1-3   2015.7

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  671. 大腸Endocytoscopyを用いた、自動診断システムの高精度化

    森 悠一, 工藤 進英, 若村 邦彦, 三澤 将史, 小川 悠史, 工藤 豊樹, 林 武雅, 宮地 英行, 片桐 敦, 石田 文生, 井上 晴洋, 二村 幸孝, 森 健策

    第34回日本医用画像工学会大会予稿集     page: OP1-1   2015.7

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  672. 開腹手術映像からの遮蔽物除去手法の基礎的検討

    北坂 孝幸, 池井 友啓, 林 祐斗, 八重嶋 秀, 澤野 弘明, 水野 慎士, 末永 康仁, 三澤 一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 139 ) page: 65-68   2015.7

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  673. `3Dプリンタ肝臓モデルを用いた手術支援の実際 ~ 手術野で使用するための工夫 ~

    田中 寛, 伊神 剛, 廣瀬 友昭, 中村 嘉彦, 江畑 智希, 横山 幸浩, 菅原 元, 水野 隆史, 小田 昌宏, 林 雄一郎, 二村 幸隆, 梛野 正人, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 139 ) page: 45-50   2015.7

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  674. 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

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 139 ) page: 39-43   2015.7

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  675. コンピュータビジョンの進化と医用画像認識理解の進化 ~ パネルディスカッション ~

    本谷 秀堅, 増谷 佳孝, 佐藤 嘉伸, 清水 昭伸, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 139 ) page: 27-32   2015.7

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  676. A Study on Improvement of Renal Artery Segmentation Using Hybrid Method

    Chenglong Wang, Mitsuru Kagajo, Yoshihiko Nakamura, Masahiro Oda, Tokunori Yamamoto, Yasushi Yoshino, Kensaku Mori

      Vol. 115 ( 139 ) page: 7-12   2015.7

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  677. シリーズ新潮流─The Next Step of Imaging Technology〈Vol.4〉3Dプリンタの医療応用最前線─利活用法から作製法まで─, 総論:3Dプリンタの医療応用の現状と展望

    森 健策

    ンナービジョン 2015年7月号   Vol. 30 ( 7 ) page: 40-44   2015.7

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  678. III Know How & Technique─3Dプリンタの技術と運用の実際 :1.臓器モデル作製のための基礎知識─プリンタ選び,臓器造形,後処理,利用法まで

    森 健策

    インナービジョン 2015年7月号   Vol. 30 ( 7 ) page: 64-71   2015.7

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  679. A Study on Improvement of Renal Artery Segmentation Using Hybrid Method

    Chenglong Wang, Mitsuru Kagajo, Yoshihiko Nakamura, Masahiro Oda, Tokunori Yamamoto, Yasushi Yoshino, Kensaku Mori

      Vol. 115 ( 139 ) page: 7-12   2015.7

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  680. A preliminary study on false positive reduction of bronchus segmentation using SVM

    Qier Meng, Takayuki Kitasaka, Hirohisa Oda, Yukitaka Nimura, Yoshihiko Nakamura, Masahiro Oda, Kensaku Mori

        page: PP30   2015.7

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  681. `3Dプリンタ肝臓モデルを用いた手術支援の実際 ~ 手術野で使用するための工夫 ~

    田中 寛, 伊神 剛, 廣瀬 友昭, 中村 嘉彦, 江畑 智希, 横山 幸浩, 菅原 元, 水野 隆史, 小田 昌宏, 林 雄一郎, 二村 幸隆, 梛野 正人, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 139 ) page: 45-50   2015.7

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  682. 3次元腹部造影CT像からの膵臓セグメンテーションにおける線状構造情報を用いた患者固有アトラス選択の有効性に関する検討

    唐澤 健一, 小田 昌宏, 林 雄一郎, 二村 幸孝, 北坂 孝幸, 三澤 一成, 藤原 道隆, 森 健策

    第34回日本医用画像工学会大会予稿集     page: OP8-4   2015.7

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  683. JOEM リポート&インフォメーション 2015-1 光部品生産技術部会 3Dプリンタを利用した新たな治療診断支援 マクロ構造からミクロ構造まで

    森 健策

    光技術コンタクト   Vol. 53 ( 6 ) page: 55   2015.6

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  684. Size-by-size iterative segmentation method of blood vessels from CT volumes and its application method of blood vessels from CT volumes and its application to renal vasculature

    Masahiro Oda, Mituru Kagajo, Tokunori Yamamoto, Yasushi Yoshino, and Kensaku Mori,

    International Journal of Computer Assisted Radiology and Surgery 2015   Vol. 10 ( 1 ) page: S208-S210   2015.6

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  685. Development of an automated method to print bronchial names on the virtual bronchial wall

    Takahiro Yamamoto, Takayuki Kitasaka, Yukitaka Nimura, Yasuhito Suenaga, and Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2015   Vol. 10 ( 1 ) page: S24-S25   2015.6

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  686. Progressive internal landmark registration for image guided vessek camping in laparoscopic gastrectomy

    Yuichiro Hayashi, Kazunari Misawa, David Hawkes, and Kensaku Mori,

    International Journal of Computer Assisted Radiology and Surgery 2015   Vol. 10 ( 1 ) page: S60-S61   2015.6

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  687. Intra-operative registration method using organ surface information for surgical navigation in laparoscopic gastrectomy

    Chihiro Morita, Yuichiro Hayashi, Oda Masahiro, David Hawkes, Kazunari Misawa, and Kensaku Mori

    International Journal of Computer Assisted Radiology and Surgery 2015   Vol. 10 ( 1 ) page: S55-S56   2015.6

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  688. Discriminative Dictionary Learning for Abdominal Multi-Organ Segmentation Reviewed

    Tong Tong, Robin Wolz, Zehan Wang, Qinquan Gao, Kazunari Misawa, Michitaka, Fujiwara, Kensaku Mori, Joseph V. Hajnal, Daniel Rueckert

    Medical Image Analysis     2015.5

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    DOI: doi:10.1016/j.media.2015.04.015

  689. 3D臓器モデルを操作デバイスとするインタラクションシステム構築に関する予備的検討

    細野 佑介, 中村嘉彦, 張 暁楠, 林 雄一郎, 小田 昌宏, 伊神 剛, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 25 ) page: 1-6   2015.5

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  690. 多元計算解剖に基づいたコンピュータ診断・治療支援システム -研究計画と研究進捗-

    森 健策, 仁木 登

    第54回 日本生体医工学会大会 プログラム・抄録集   Vol. 53 ( 1 ) page: 144   2015.5

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  691. A study on bronchus segmentation based on machine learning method from chest CT Image

    Qier Meng, Takayuki Kitasaka, Yukitaka Nimura, Yoshihoko Nakamura, Masahiro Oda, Kensaku Mori

      Vol. 115 ( 25 ) page: 121-126   2015.5

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  692. A study on bronchus segmentation based on machine learning method from chest CT Image

    Qier Meng, Takayuki Kitasaka, Yukitaka Nimura, Yoshihoko Nakamura, Masahiro Oda, Kensaku Mori

      Vol. 115 ( 25 ) page: 121-126   2015.5

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  693. 3D臓器モデルを操作デバイスとするインタラクションシステム構築に関する予備的検討

    細野 佑介, 中村嘉彦, 張 暁楠, 林 雄一郎, 小田 昌宏, 伊神 剛, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 115 ( 25 ) page: 1-6   2015.5

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  694. 臓器情報を利用した血管名自動対応付け手法の検討

    加賀城 充, 中村 嘉彦, 林 雄一郎, 小田 昌宏, 三澤 一成, 森 健策

    電子情報通信学会 2015年総合大会プログラム     page: 76   2015.3

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  695. 腹腔鏡下手術ナビゲーションにおける血管と臓器情報を用いた術中のレジストレーション手法に関する初期検討

    林 雄一郎, 森田 千尋, ホークス デイビット, 三澤 一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 114 ( 482 ) page: 321-325   2015.3

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  696. 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

    電子情報通信学会技術研究報告(MI)   Vol. 114 ( 482 ) page: 311-316   2015.3

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  697. X線暗視野法光学系を用いた屈折X線イメージングによる医用画像工学の創成と多元計算解剖学への展開

    安藤 正海, 湯浅 哲也, 砂口 尚輝, 森 健策, 鈴木 芳文, 市原 周, Rajiv Gupta

    電子情報通信学会技術研究報告(MI)   Vol. 114 ( 482 ) page: 295-300   2015.3

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  698. 気管支内腔壁面への気管支枝名自動表示手法の開発

    山本 貴洋, 北坂 孝幸, 二村 幸孝, 末永 康仁, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 114 ( 482 ) page: 253-258   2015.3

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  699. 大腸ひだ検出処理に基づく大腸内視鏡ナビゲーションシステムに関する検討

    近藤 弘明, 小田 昌宏, 古川 和宏, 宮原 良二, 廣岡 芳樹, 後藤 秀美, 北坂 孝幸, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 114 ( 482 ) page: 237-242   2015.3

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  700. SVMを利用した3次元腹部CT像からの胆管領域セグメンテーション手法の開発

    古閑 楠人, 林 雄一郎, 廣瀬 友昭, 小田 昌宏, 北坂 孝幸, 伊神 剛, 梛野 正人, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 114 ( 482 ) page: 227-232   2015.3

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  701. 術中音声操作に基づく手術ナビゲーションにおけるユーザインタフェースの改良

    林 雅大, 道満 恵介, 目加田 慶人, 三澤 一成, 森 健策

    電子情報通信学会技術研究報告(MI)   Vol. 114 ( 482 ) page: 129-132   2015.3

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  702. 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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  703. 特集 RSNA 2014 A Century of Transforming Medicine:15. 3Dプリンタ,ユーザーインターフェイスの動向を中心に

    森 健策

    インナービジョン 2015年2月号   Vol. 30 ( 2 ) page: 46-47   2015.2

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  704. マイクロCTを使用した三次元肺末梢構造の観察

    本間 裕敏, 高畠 博嗣, 森 雅樹, 名取 博, 小田 昌宏, 森 健策

    '第7回 呼吸機能イメージング研究会学術集会     page: 78   2015.2

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  705. Meclozine Promotes Longitudinal Skeletal Growth in Transgenic Mice with Achondroplasia Carrying a Gainof-Function Mutation in the FGFR3 Gene

    Masaki Matsushita, Satoru Hasegawa, Hiroshi Kitoh, Kensaku Mori, Bisei Ohkawara, Akihiro Yasoda, Akio Masuda, Naoki Ishiguro, Kinji Ohno

    Endocrinology   Vol. 156 ( 2 ) page: 548-554   2015.2

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  706. Connection method of separated luminal regions of intestine from CT volumes

    Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Osamu Watanabe, Takafumi Ando, Yoshiki Hirooka, Hidemi Goto, and Kensaku Mori

    SPIE Medcal. Imaging 2015     page: accepted   2015.2

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  707. Automated branching pattern report generation for laparoscopic surgery assistance

    Masahiro Oda, Tetsuro Matsuzaki, Yuichiro Hayashi, Takayuki Kitasaka, Kazunari Misawa, and Kensaku Mori

    SPIE Medical Imaging 2015     page: accepted   2015.2

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  708. Investigation of Optimal Feature Value Set in False Positive Reduction Process for Automated Abdominal Lymph Node Detection Method

    Yoshihiko Nakamura, Yukitaka Nimura, Takayuki Kitasaka, Shinji Mizuno, Kazuhiro Furukawa, Hidemi Goto, Michitaka Fujiwara, Kazunari Misawa, Masaki Ito, Shigeru Nawano, and Kensaku Mori

    SPIE Medical Imaging 2015     page: accepted   2015.2

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  709. Pancreas segmentation from 3D abdominal CT images using patient-specific weighted-subspatial probabilistic atlases

    Kenichi Karasawa, Masahiro Oda, Yuichiro Hayashi, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, and Kensaku Mori

    SPIE Medical Imaging 2015     page: accepted   2015.2

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  710. 医用画像処理と3Dプリンタによる臓器モデル生成と診断治療支援への応用

    森 健策

    電子情報通信学会 2015年総合大会プログラム     page: CS-4-8, p.65   2015.2

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  711. 3Dプリンティングの現状と将来展望:医用画像処理と3Dプリンタによる臓器実体モデル作成とその利用'

    森 健策

    光技術コンタクト   Vol. 53 ( 2 ) page: 20-27   2015.2

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  712. A Model-free Method for Annotating on Vascular Structure in Volume Rendered Images

    Wei He, Yanfang Li, Weili Shi, Yu Miao, Fei He, Fei Yan,, Huamin Yang, Huimao Zhang, Kensaku Mori, and Zhengang Jiang

    Proceedings of SPIE   Vol. 9415   page: 941528-1-8   2015.2

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    Language:English  

  713. Development And Clinical Application of Surgical Navigation System for Laparoscopic Hepatectomy

    Yuichiro Hayashi, Tsuyoshi Igami, Tomoaki Hirose, Masato Nagino, and Kensaku Mori

    Proceedings of SPIE   Vol. 9715   page: 94151X-1-6   2015.2

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    Language:English  

  714. Automated Torso Organ Segmentation from 3D CT Images using Structured Perceptron and Dual Decomposition

    Yukitaka Nimura, Yuichiro Hayashi, Kazunari Misawa, and Kensaku Mori

    Proceedings of SPIE   Vol. 9414   page: 94143L-1-6   2015.2

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  715. Adaptive marker-free registration using a multiple point strategy for real-time and robust endoscope electromagnetic navigation Reviewed

    Xiongbiao Luo, Ying Wan, Xiangjian He, and Kensaku Mori

    Computer Methods and Programs in Biomedicine   Vol. 118 ( 2 )   2015.2

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

    DOI: doi:10.1016/j.cmpb.2014.11.008

  716. Adaptive marker-free registration using a multiple point strategy for real-time and robust endoscope electromagnetic navigation Reviewed

    Xiongbiao Luo, Ying Wan, Xiangjian He, Kensaku Mori

    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE   Vol. 118 ( 2 ) page: 147 - 157   2015.2

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:ELSEVIER IRELAND LTD  

    Registration of pre-clinical images to physical space is indispensable for computer-assisted endoscopic interventions in operating rooms. Electromagnetically navigated endoscopic interventions are increasingly performed at current diagnoses and treatments. Such interventions use an electromagnetic tracker with a miniature sensor that is usually attached at an endoscope distal tip to real time track endoscope movements in a pre-clinical image space. Spatial alignment between the electromagnetic tracker (or sensor) and pre-clinical images must be performed to navigate the endoscope to target regions. This paper proposes an adaptive marker-free registration method that uses a multiple point selection strategy. This method seeks to address an assumption that the endoscope is operated along the centerline of an intraluminal organ which is easily violated during interventions. We introduce an adaptive strategy that generates multiple points in terms of sensor measurements and endoscope tip center calibration. From these generated points, we adaptively choose the optimal point, which is the closest to its assigned the centerline of the hollow organ, to perform registration. The experimental results demonstrate that our proposed adaptive strategy significantly reduced the target registration error from 5.32 to 2.59 mm in static phantoms validation, as well as from at least 7.58 mm to 4.71 mm in dynamic phantom validation compared to current available methods. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

    DOI: 10.1016/j.cmpb.2014.11.008

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  717. A Model-free Method for Annotating on Vascular Structure in Volume Rendered Images

    Wei He, Yanfang Li, Weili Shi, Yu Miao, Fei He, Fei Yan, Huamin Yang, Huimao Zhang, Kensaku Mori, Zhengang Jiang

    Proceedings of SPIE   Vol. 9415   page: 941528-1-8   2015.2

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    Language:English   Publishing type:Research paper (other academic)  

  718. 3Dプリンティングの現状と将来展望:医用画像処理と3Dプリンタによる臓器実体モデル作成とその利用'

    森 健策

    光技術コンタクト   Vol. 53 ( 2 ) page: 20-27   2015.2

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

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