Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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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

Polyp size classification in colorectal cancer using a Siamese network

page： OP2-14 2019.7

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

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

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

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

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

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

Artificial intelligence and colonoscopy: Current status and future perspectives. Reviewed International journal

Kudo SE, Mori Y, Misawa M, Takeda K, Kudo T, Itoh H, Oda M, Mori K

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society Vol. 31 ( 4 ) page： 363 - 371 2019.7

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

BACKGROUND AND AIM: Application of artificial intelligence in medicine is now attracting substantial attention. In the field of gastrointestinal endoscopy, computer-aided diagnosis (CAD) for colonoscopy is the most investigated area, although it is still in the preclinical phase. Because colonoscopy is carried out by humans, it is inherently an imperfect procedure. CAD assistance is expected to improve its quality regarding automated polyp detection and characterization (i.e. predicting the polyp's pathology). It could help prevent endoscopists from missing polyps as well as provide a precise optical diagnosis for those detected. Ultimately, these functions that CAD provides could produce a higher adenoma detection rate and reduce the cost of polypectomy for hyperplastic polyps. METHODS AND RESULTS: Currently, research on automated polyp detection has been limited to experimental assessments using an algorithm based on ex vivo videos or static images. Performance for clinical use was reported to have >90% sensitivity with acceptable specificity. In contrast, research on automated polyp characterization seems to surpass that for polyp detection. Prospective studies of in vivo use of artificial intelligence technologies have been reported by several groups, some of which showed a >90% negative predictive value for differentiating diminutive (≤5 mm) rectosigmoid adenomas, which exceeded the threshold for optical biopsy. CONCLUSION: We introduce the potential of using CAD for colonoscopy and describe the most recent conditions for regulatory approval for artificial intelligence-assisted medical devices.

DOI： 10.1111/den.13340

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

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

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

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

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

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

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

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

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

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

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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Papers - MORI, Kensaku