Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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複数フレームのステレオ内視鏡画像を用いた臓器表面形状復元に関する検討

柴田睦実，林雄一郎，小田昌宏，三澤一成，森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 326-327 2017.10

気管支鏡追跡における ORB-SLAM 適用に関する初期的検討

王成，小田昌宏，林雄一郎，森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 324-325 2017.10

μCT 画像を用いた大変形を含む連続切片 HE 染色画像の 3 次元再構築

長柄快，Holger Roth，中村彰太，小田紘久，守谷享泰，小田昌宏，森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 363-364 2017.10

色ヒストグラム特徴を用いた腹腔鏡手術映像の体外・体内シーン分類

山田和希, 道満恵介, 目加田慶人, 三澤一成, 森健策

平成 29 年度日本生体医工学会東海支部大会プログラム・抄録集 page： 00 2017.10

Automatic Segmentation of Head Anatomical Structures from Sparsely-annotated Images Reviewed

Takaaki Sugino, Holger R. Roth, Mohammad Eshghi, Masahiro Oda, Min Suk Chung, Kensaku Mori

IEEE International Conference on Cyborg and Bionic Systems page： 145-149 2017.10

3D Fully Convolutional Networks と全連結条件付確率場による 3 次元 CT 画像からの多臓器自動抽出に関する検討

楊瀛, 小田昌宏, Roth Holger, 北坂孝幸, 三澤一成, 森健策

日本コンピュータ外科学会誌第26回日本コンピュータ外科学会大会特集号 Vol. 19 ( 4 ) page： 268-269 2017.10

畳み込みニューラルネットワークを利用した超拡大大腸内視鏡画像における腫瘍・非腫瘍の分類

伊東隼人, 森悠一, 三澤将史, 小田昌宏, 工藤進英, 森健策

電子情報通信学会技術研究報告(MI) Vol. 117 ( 220 ) page： 17-21 2017.9

Micro-CT Guided 3D Reconstruction of Histological images

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

LNCS 10530 page： 93-101 2017.9

Motion Vector for Outlier Elimination in Feature Matching and Its Application in SLAM Based Laparoscopic Tracking

Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Holger Roth, Kensaku Mori

LNCS 10550 page： 60-69 2017.9

3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation

Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken'ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori

LNCS 10553 page： 222-230 2017.9

3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation

Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken'ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori

LNCS 10553 page： 222-230 2017.9

Virtual 3D microscope and magnified 3D print for naked eye analyses of alveoli and alveolar duct structures by Heitzman lung specimen with micro CT

Hiroshi Natori, Masaki Mori, Hirotsugu Takabatake, Hirotoshi Homma, ensaku Mori, Masahiro Oda, Hiroyuki Koba, Hiroki Takahashi

ERS International congress 2017 page： Session 439 2017.9

Tracking and Segmentation of the Airways in Chest CT Using a Fully Convolutional Network

Qier Meng, Holger R. Roth, Takayuki Kitasaka, Masahiro Oda, Junji Ueno, Kensaku Mori

LNCS 10434 page： 198-207 2017.9

TBS: Tensor-Based Supervoxels for Unfolding the Heart

Hirohisa Oda, Holger R. Roth, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Julia A. Schnabel, Kensaku Mori

LNCS 10433 page： 681-689 2017.9

Accuracy of diagnosing invasive colorectal cancer using computer-aided endocytoscopy Reviewed

Kenichi Takeda, Shin-ei Kudo, Yuichi Mori, Masashi Misawa, Toyoki Kudo, Kunihiko Wakamura, Atsushi Katagiri, Toshiyuki Baba, Eiji Hidaka, Fumio Ishida, Haruhiro Inoue, Masahiro Oda, Kensaku Mori

ENDOSCOPY Vol. 49 ( 8 ) page： 798 - 802 2017.8

Language：English Publishing type：Research paper (scientific journal) Publisher：GEORG THIEME VERLAG KG

Background and study aims Invasive cancer carries the risk of metastasis, and therefore, the ability to distinguish between invasive cancerous lesions and less-aggressive lesions is important. We evaluated a computer-aided diagnosis system that uses ultra-high (approximately x 400) magnification endocytoscopy (EC-CAD).
Patients and methods We generated an image database from a consecutive series of 5843 endocytoscopy images of 375 lesions. For construction of a diagnostic algorithm, 5543 endocytoscopy images from 238 lesions were randomly extracted from the database for machine learning. We applied the obtained algorithm to 200 endocytoscopy images and calculated test characteristics for the diagnosis of invasive cancer. We defined a high-confidence diagnosis as having a >= 90% probability of being correct.
Results Of the 200 test images, 188 (94.0%) were assessable with the EC-CADsystem. Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were 89.4%, 98.9%, 94.1%, 98.8%, and 90.1 %, respectively. High-confidence diagnosis had a sensitivity, specificity, accuracy, PPV, and NPV of 98.1%, 100%, 99.3%, 100 %, and 98.8%, respectively.
Conclusion: EC-CADmay be a useful tool in diagnosing invasive colorectal cancer.

DOI： 10.1055/s-0043-105486

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure Reviewed Open Access

Kenichi Karasawa, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Chengwen Chu, Guoyan Zheng, Daniel Rueckert, Kensaku Mori

Medical Image Analysis Vol. 39 page： 18-28 2017.7

K-means 法と Joint Unsupervised Learning による3次元医用画像の教師なしセグメンテーション

守谷享泰, Holger R. Roth, 中村彰太, 小田紘久, 長柄快, 小田昌宏, 森健策

第36回日本医用画像工学会大会予稿集 page： OP16-5 2017.7

条件付き確率場による医用画像からの多臓器抽出におけるHigher Order Potential とボクセル連結構造の影響に関する考察

楊瀛, 小田昌宏, Roth Holger, 北坂孝幸, 三澤一成, 森健策

第36回日本医用画像工学会大会予稿集 page： OP16-4 2017.7

3DU-Netによる3次元胸部CT像からのリンパ節検出

小田紘久, KanwalK.Bhatia, HolgerR.Roth, 小田昌宏, 北坂孝幸, 岩野信吾, 本間裕敏, 高畠博嗣, 森雅樹, 名取博 ,JuliaA.Schnabel, 森健策

第36回日本医用画像工学会大会予稿集 page： OP1-6 2017.7

Torso organ segmentation in CT using fine-tuned 3D fully convolutional networks

Holger ROTH,Ying YANG,Masahiro ODA,Hirohisa ODA, Yuichiro HAYASHI,Natsuki SHIMIZU,Takayuki KITASAKA,Michitaka FUJIWARA,Kazunari MISAWA,Kensaku MORI

page： OP1-8 2017.7

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Papers - MORI, Kensaku