研究者詳細 - 森　健策

論文 - 森　健策

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Unsupervised segmentation of 3D medical images based on clustering and deep representation learning Open Access

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

Proc. SPIE 10578, Medical Imaging 2018 頁： 105780-1-105780-7 2018年2月

Unsupervised pathology image segmantaion using representation learning with spherical k-means Open Access

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

Proc. SPIE 10581, Medical Imaging 2018 頁： 1058111-1-1058111-7 2018年2月

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional network Open Access

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

Proc. SPIE 10574, Medical Imaging 2018 頁： 105740B-1-105740B-6 2018年2月

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 頁： 10740K-1-10740K-7 2018年2月

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 頁： 105761Y-1-10576Y-6 2018年2月

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 74 巻 ( 2 ) 頁： 175-190 2018年2月

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 74 巻 ( 2 ) 頁： 175-190 2018年2月

術前術中後診断治療支援

森　健策

月刊「細胞] 50 巻 ( 1 ) 頁： 14-18 2018年1月

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 33 巻 ( 2 ) 頁： 35-36 2018年1月

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 33 巻 ( 2 ) 頁： 35-36 2018年1月

Advanced Endoscopic Navigation: Surgical Big Data, Methodology, and Applications 査読有り

Luo Xiongbiao, Mori Kensaku, Peters Terry M.

ANNUAL REVIEW OF BIOMEDICAL ENGINEERING, VOL 20 20 巻 ( 1 ) 頁： 221 - 251 2018年

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Annual Review of Biomedical Engineering

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

A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multi-organ Segmentation 招待有り査読有り

Roth, HR; Shen, C; Oda, H; Sugino, T; Oda, M; Hayashi, Y; Misawa, K; Mori, K

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT IV 11073 巻頁： 417 - 425 2018年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Recent advances in deep learning, like 3D fully convolutional networks (FCNs), have improved the state-of-the-art in dense semantic segmentation of medical images. However, most network architectures require severely downsampling or cropping the images to meet the memory limitations of today’s GPU cards while still considering enough context in the images for accurate segmentation. In this work, we propose a novel approach that utilizes auto-context to perform semantic segmentation at higher resolutions in a multi-scale pyramid of stacked 3D FCNs. We train and validate our models on a dataset of manually annotated abdominal organs and vessels from 377 clinical CT images used in gastric surgery, and achieve promising results with close to 90% Dice score on average. For additional evaluation, we perform separate testing on datasets from different sources and achieve competitive results, illustrating the robustness of the model and approach.

DOI： 10.1007/978-3-030-00937-3_48

Web of Science

Scopus

その他リンク： https://dblp.uni-trier.de/db/conf/miccai/miccai2018-4.html#RothSOSOHMM18

[Implementation of artificial intelligence into colonoscopy: experience of research and development of computer-aided diagnostic system for endocytoscopy]. 査読有り

Mori Y, Kudo SE, Mori K

Nihon Shokakibyo Gakkai zasshi = The Japanese journal of gastro-enterology 115 巻 ( 12 ) 頁： 1030 - 1036 2018年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：一般財団法人日本消化器病学会

<p>近年の内視鏡イメージング技術の発展により，大腸病変の内視鏡診断は飛躍的に発展した．しかし同時に，高精度の診断はエキスパート内視鏡医しか実現できないという，ジレンマが明らかになりつつある．このような内視鏡診断能力の限界に対する，革新的な解決策として注目をあびているのが人工知能による内視鏡診断支援システム（computer-aided diagnosis；CAD）である．本稿では内視鏡CADの研究開発の現状について概観した後，医工産官連携プロジェクト（代表研究者：工藤進英）として研究を進めているEndocyto（=520倍ズームの超拡大内視鏡）を用いた内視鏡CADの発案・医師主導研究・薬機法承認申請の取り組みについて紹介する．</p>

DOI： 10.11405/nisshoshi.115.1030

PubMed

CiNii Research

Application of three-dimensional print in minor hepatectomy following liver partition between anterior and posterior sectors 査読有り

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年12月

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

MI2017-58 117 巻 ( 281 ) 頁： 47-52 2017年11月

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

MI2017-51 117 巻 ( 281 ) 頁： 15-20 2017年11月

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 頁： 224 2017年11月

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 頁： 267 2017年11月

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 頁： 179 2017年11月

3Dプリンターの基礎と医療応用 Open Access

森健策

月刊心臓 49 巻 ( 11 ) 頁： 1104-1113 2017年11月

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