研究者詳細 - 森　健策

論文 - 森　健策

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Robust colonoscope tracking method for colon deformations utilizing coarse-to-fine correspondence findings 査読有り

Oda, M; Kondo, H; Kitasaka, T; Furukawa, K; Miyahara, R; Hirooka, Y; Goto, H; Navab, N; Mori, K

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 12 巻 ( 1 ) 頁： 39 - 50 2017年1月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：International Journal of Computer Assisted Radiology and Surgery

Purpose: 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. Method: 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. Result: 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. Conclusions: 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

Web of Science

Scopus

PubMed

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 32 巻 ( 2 ) 頁： 44-45 2017年1月

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

Meng Qier, Kitasaka Takayuki, Oda Masahiro, Mori Kensaku

MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS 10134 巻頁： 101370M-1-101370M-9 2017年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：Progress in Biomedical Optics and Imaging - Proceedings of SPIE

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頁： 35-41 2017年

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

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

MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS 10134 巻頁： 101343H-1-101343H-12 2017年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：Progress in Biomedical Optics and Imaging - Proceedings of SPIE

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 頁： 183 2016年12月

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 頁： 214 2016年12月

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 頁： 151 2016年11月

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 頁： 94 2016年11月

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) 18 巻 ( 4 ) 頁： 367-368 2016年11月

腹腔鏡ナビゲーションシステムにおける ORB-SLAM の適用に関する初期的検討

王成, Mohammad Eshghi, 小田昌宏, 林雄一郎, 三澤一成, 蒋振剛, 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) 18 巻 ( 4 ) 頁： 355-356 2016年11月

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) 18 巻 ( 4 ) 頁： 365-366 2016年11月

腹腔鏡下胃切除術におけるポート位置決定支援のためのポート位置プランニングシステムの開発

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) 18 巻 ( 4 ) 頁： 350-351 2016年11月

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) 18 巻 ( 4 ) 頁： 246-247 2016年11月

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) 18 巻 ( 4 ) 頁： 287-288 2016年11月

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) 18 巻 ( 4 ) 頁： 290-291 2016年11月

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) 18 巻 ( 4 ) 頁： 293-294 2016年11月

テンソルベースグラフカットを用いた血管抽出手法の実質臓器への応用

王成龍, 小田昌宏, 吉野能, 山本徳則, 伊神剛, 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) 18 巻 ( 4 ) 頁： 295-296 2016年11月

From macro-scale to micro-scale computational anatomy: perspective of the next 20 years 査読有り

Kensaku Mori

Medical Image Analysis 2016年10月

Tensor-Based Graph-Cut in Riemannian Metric Space and Its Application to Renal Artery Segmentation

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

MICCAI 2016 LNCS 9902 巻頁： 353-361 2016年10月

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