Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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MISTライブラリのためのGPUプログラミング

小田紘久, 小田昌宏, 北坂孝幸, 森健策

電子情報通信学会技術研究報告(MI) Vol. 116 ( 393 ) page： 133-136 2017.1

Deep-Learning-Based Segmentation for the Head Sectioned Images of the Visible Korean Project

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

MI2016-119 Vol. 116 ( 393 ) page： 191-194 2017.1

Influence of Voxel-Connection Structure in Organ Segmentation Based on Conditional Random Field

Ying Yang, Masahiro Oda, Kazunari Misawa, Daniel Rueckert, Kensaku Mori

MI2016-112 Vol. 116 ( 393 ) page： 157-162 2017.1

MICCAI 2016参加報告

小田昌宏, 宮内翔子, 諸岡健一, 周向栄, 増谷佳孝, 中口俊哉, 井宮淳, 森健策

電子情報通信学会技術研究報告(MI) Vol. 116 ( 393 ) page： 185-190 2017.1

3Dプリンタ・ユーザーインターフェイス等の最新動向

森健策

インナービジョン 2017年2月号 Vol. 32 ( 2 ) page： 44-45 2017.1

Robust colonoscope tracking method for colon deformations utilizing coarse-to-fine correspondence findings Reviewed Open Access

Masahiro Oda, Hiroaki Kondo, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Nassir Navab, Kensaku Mori

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY Vol. 12 ( 1 ) page： 39 - 50 2017.1

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

Polyps found during CT colonography can be removed by colonoscopic polypectomy. A colonoscope navigation system that navigates a physician to polyp positions while performing the colonoscopic polypectomy is required. Colonoscope tracking methods are essential for implementing colonoscope navigation systems. Previous colonoscope tracking methods have failed when the colon deforms during colonoscope insertions. This paper proposes a colonoscope tracking method that is robust against colon deformations.
The proposed method generates a colon centerline from a CT volume and a curved line representing the colonoscope shape (colonoscope line) by using electromagnetic sensors. We find correspondences between points on a deformed colon centerline and colonoscope line by a landmark-based coarse correspondence finding and a length-based fine correspondence finding processes. Even if the coarse correspondence finding process fails to find some correspondences, which occurs with colon deformations, the fine correspondence finding process is able to find correct correspondences by using previously recorded line lengths.
Experimental results using a colon phantom showed that the proposed method finds the colonoscope tip position with tracking errors smaller than 50 mm in most trials. A physician who specializes in gastroenterology commented that tracking errors smaller than 50 mm are acceptable. This is because polyps are observable from the colonoscope camera when positions of the colonoscope tip and polyps are closer than 50 mm.
We developed a colonoscope tracking method that is robust against deformations of the colon. Because the process was designed to consider colon deformations, the proposed method can track the colonoscope tip position even if the colon deforms.

DOI： 10.1007/s11548-016-1456-6

3Dプリンタ・ユーザーインターフェイス等の最新動向

森健策

インナービジョン 2017年2月号 Vol. 32 ( 2 ) page： 44-45 2017.1

Airway extraction from 3D chest CT volumes based on iterative extension of VOI enhanced by cavity enhancement filter

Qier Meng, Takayuki Kitasaka, Masahiro Oda, Kensaku Mori

MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS Vol. 10134 page： 101370M-1-101370M-9 2017

Language：English Publishing type：Research paper (international conference proceedings) Publisher：SPIE-INT SOC OPTICAL ENGINEERING

Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining an integrated 3-D airway tree structure from a CT volume is a quite challenging task. This paper presents a novel airway segmentation method based on intensity structure analysis and bronchi shape structure analysis in volume of interest (VOI). This method segments the bronchial regions by applying the cavity enhancement filter (CEF) to trace the bronchial tree structure from the trachea. It uses the CEF in each VOI to segment each branch and to predict the positions of VOIs which envelope the bronchial regions in next level. At the same time, a leakage detection is performed to avoid the leakage by analysing the pixel information and the shape information of airway candidate regions extracted in the VOI. Bronchial regions are finally obtained by unifying the extracted airway regions. The experiments results showed that the proposed method can extract most of the bronchial region in each VOI and led good results of the airway segmentation.

DOI： 10.1117/12.2254233

Web of Science

Scopus

かがくゼミナール「立体臓器モデルを作ろう」実施報告

森健策, 長柄快, 舘高基, 伊神剛, 堀内智子

名古屋市科学館紀要 page： 35-41 2017

An improved method for pancreas segmentation using SLIC and interactive region merging

Liyuan Zhang, Huamin Yang, Weili Shi, Yu Miao, Qingliang Li, Fei He, Wei He, Yanfang Li, Huimao Zhang, Kensaku Mori, Zhengang Jiang

MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS Vol. 10134 page： 101343H-1-101343H-12 2017

Language：English Publishing type：Research paper (international conference proceedings) Publisher：SPIE-INT SOC OPTICAL ENGINEERING

Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.

DOI： 10.1117/12.2254366

Web of Science

Scopus

Myofiber Visualization System for Micro CT Volumes of Left Ventricle

Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF page： 183 2016.12

Quantitative Analysis of Renal Dominant Regions based on Precise Renal Artery Segmentation'

Chenglong Wang, Yoshihiko Nakamura, Masahiro Oda, Yasushi Yoshino, Tokunori Yamamoto, Kensaku Mori

RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF page： 214 2016.12

Naked Eye Visible Pores of Kohn and the Shapes of Alveoli on Magnified Three Dimensional Printed Model of the Lung Specimen by Virtual Image of Micro CT: Initial Experience

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

RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF page： 151 2016.11

Visualization Method of Myofiber Structure of the Left Ventricle Apex from Micro CT Volumes

Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

RSNA 2016 (Radiological Society of North America) Scientific Assembly and Annual Meeting PROGRAM IN BRIEF page： 94 2016.11

ステレオ内視鏡画像からの臓器形状復元手法における誤対応点削減処理の提案と手術画像への適用

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25回日本コンピュータ外科学会大会特集号(JSCAS2016) Vol. 18 ( 4 ) page： 367-368 2016.11

回帰木を用いたCT画像における臓器の局所化に関する特徴量の検討

清水南月, 小田昌宏, 三澤一成, 藤原道隆, 森健策

日本コンピュータ外科学会誌第25回日本コンピュータ外科学会大会特集号(JSCAS2016) Vol. 18 ( 4 ) page： 365-366 2016.11

脳神経外科手術ナビゲーションのためのステレオ画像からの脳表の3次元形状の復元

Mohammad Eshghi, 林雄一郎, 柴田睦実, 小田昌宏, 藤井正純, 森健策

日本コンピュータ外科学会誌第25回日本コンピュータ外科学会大会特集号(JSCAS2016) Vol. 18 ( 4 ) page： 246-247 2016.11

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に関する初期的検討～統計的特徴量を利用したリンパ節検出率の改善～

寶珠山裕, Holger R.Roth, 小田昌宏, 中村嘉彦, 三澤一成, 藤原道隆, 森健策

日本コンピュータ外科学会誌第25回日本コンピュータ外科学会大会特集号(JSCAS2016) Vol. 18 ( 4 ) page： 287-288 2016.11

位置関係を用いた特徴量の導入による胆道領域セグメンテーション手法の改善

陳鵬飛, 田中寛, 小田紘久, 小田昌宏, 林雄一郎,伊神剛, 椰野正人, 森健策

日本コンピュータ外科学会誌第25回日本コンピュータ外科学会大会特集号(JSCAS2016) Vol. 18 ( 4 ) page： 290-291 2016.11

血管木構造構築手法の改善とその血管名称自動対応付けへの応用

張暁楠, 加賀城充, 小田昌宏, 林雄一郎, 三澤一成, 森健策

日本コンピュータ外科学会誌第25回日本コンピュータ外科学会大会特集号(JSCAS2016) Vol. 18 ( 4 ) page： 293-294 2016.11

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Papers - MORI, Kensaku