Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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森健策

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

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

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

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

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

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

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

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

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

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

Joint multi organ and tumor segmentation from partial labels using federated learning Invited 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 Vol. 13573 page： 58 - 67 2022

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

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

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

Scopus

PubMed

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

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

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

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

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

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

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

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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Papers - MORI, Kensaku