Faculty Profiles - ODA, Masahiro

Papers - ODA, Masahiro

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腹腔鏡動画像用オンラインアノテーションツールの開発

屠芸豪, 伊東隼人, 小澤卓也, 小田昌宏, 竹下修由, 伊藤雅昭, 森健策

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

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

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

Gastroenterology 2020.9

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

大腸内視鏡における穿孔の自動検出および位置推定に関する予備的検討

蒋凱, 伊東隼人, 小田昌宏, 奥村大志, 森悠一, 三澤将史, 林武雅, 工藤進英, 森健策

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

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

御手洗翠, 小田紘久, 杉野貴明, 守谷享泰, 伊東隼人, 小田昌宏, 小宮山琢真, 古川和宏, 宮原良二, 藤城光弘, 森雅樹, 高畠博嗣, 名取博, 森健策

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

Language：Japanese Publisher：日本医用画像工学会

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

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

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

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

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

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

Gastrointestinal endoscopy 2020.7

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

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

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

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

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

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

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

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

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

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

森悠一, 工藤進英, 三澤将史, 武田健一, 前田康晴, 小川悠史, 一政克朗, 若村邦彦, 林武雅, 工藤豊樹, 宮地英行, 馬場俊之, 伊東隼人, 小田昌宏, 森健策

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

Language：Japanese Publisher：(社)日本大腸検査学会

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

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AIによるSSA/Pの超拡大内視鏡診断

小川悠史, 工藤進英, 森悠一, 三澤将史, 片岡伸一, 前田康晴, 一政克朗, 石垣智之, 工藤豊樹, 若村邦彦, 林武雅, 馬場俊之, 石田文生, 伊東隼人, 小田昌宏, 森健策

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

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

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

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

Language：English Publishing type：Research paper (scientific journal) Publisher：日本医用画像工学会

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

arXiv

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Other Link： http://arxiv.org/pdf/2004.03272v1

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

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

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

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

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

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

Language：Japanese Publisher：Techniques and Innovations in Gastrointestinal Endoscopy

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

DOI： 10.1016/j.tgie.2019.150632

Web of Science

Scopus

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

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

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

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

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

MEDICAL IMAGE ANALYSIS Vol. 60 page： 101623 2020.2

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

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

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

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

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

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

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

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

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

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Papers - ODA, Masahiro