Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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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

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

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

Web of Science

Scopus

PubMed

機械学習を用いた内視鏡画像自動診断 Open Access

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

Artificial Intelligence for Endocytoscopy Provides Fully Automated Diagnosis of Histological Remission in Ulcerativ E. Coli Tis Invited Reviewed

Maeda Yasuharu, Shinei Kudo, Yuichi Mori, Masashi Misawa, Kunihiko Wakamura, Seiko Hayashi, Noriyuki Ogata, Kenichi Takeda, Toyoki Kudo, Takemasa Hayashi, Atsushi Katagiri, Fumio Ishida, Kazuo Ohtsuka, Masahiro Oda, Kensaku Mori

GASTROINTESTINAL ENDOSCOPY Vol. 85 ( 5 ) page： AB248 - AB248 2017.5

3Dプリンタの医療応用 Open Access

森　健策

医用画像情報学会雑誌 Vol. 34 ( 1 ) page： 1-6 2017.4

3Dプリンタの医療応用 Open Access

森健策

医用画像情報学会雑誌 Vol. 34 ( 1 ) page： 1-6 2017.4

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

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

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

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

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

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

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 AND SURGERY Vol. 12 ( 2 ) page： 245 - 261 2017.2

Language：English Publishing type：Research paper (scientific journal) Publisher：SPRINGER HEIDELBERG

Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3D airway tree structure from a CT volume is quite a challenging task. Several researchers have proposed automated airway segmentation algorithms basically based on region growing and machine learning techniques. However, these methods fail to detect the peripheral bronchial branches, which results in a large amount of leakage. This paper presents a novel approach for more accurate extraction of the complex airway tree.
This proposed segmentation method is composed of three steps. First, Hessian analysis is utilized to enhance the tube-like structure in CT volumes; then, an adaptive multiscale cavity enhancement filter is employed to detect the cavity-like structure with different radii. In the second step, support vector machine learning will be utilized to remove the false positive (FP) regions from the result obtained in the previous step. Finally, the graph-cut algorithm is used to refine the candidate voxels to form an integrated airway tree.
A test dataset including 50 standard-dose chest CT volumes was used for evaluating our proposed method. The average extraction rate was about 79.1 % with the significantly decreased FP rate.
A new method of airway segmentation based on local intensity structure and machine learning technique was developed. The method was shown to be feasible for airway segmentation in a computer-aided diagnosis system for a lung and bronchoscope guidance system.

DOI： 10.1007/s11548-016-1492-2

Web of Science

Scopus

PubMed

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

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

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

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

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

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

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

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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Papers - MORI, Kensaku