Generalized N-Dimensional Sparse Coding and Its Application to Computational Anatomy Models
Project/Area Number |
24300076
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Research Category |
Grant-in-Aid for Scientific Research (B)
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Allocation Type | Partial Multi-year Fund |
Section | 一般 |
Research Field |
Perception information processing/Intelligent robotics
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Research Institution | Ritsumeikan University |
Principal Investigator |
CHEN YAN WEI 立命館大学, 情報理工学部, 教授 (60236841)
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Co-Investigator(Kenkyū-buntansha) |
TANAKA T, Hiromi 立命館大学, 情報理工学部, 教授 (10268154)
HAN Xian-Hua 立命館大学, 立命館グローバルイノベーション研究機構, 准教授 (60469195)
SATO Yoshinobu 奈良先端科学技術大学院大学, 情報科学研究科, 教授 (70243219)
FURUKAWA Akira 首都大学東京, 人間健康科学研究科, 教授 (80199421)
MORIKAWA Shigehiro 滋賀医科大学, 医学部, 教授 (60220042)
TATEYAMA Tomoko 立命館大学, 情報理工学部, 助手 (90550153)
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Project Period (FY) |
2012-04-01 – 2015-03-31
|
Project Status |
Completed (Fiscal Year 2014)
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Budget Amount *help |
¥16,250,000 (Direct Cost: ¥12,500,000、Indirect Cost: ¥3,750,000)
Fiscal Year 2014: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2013: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2012: ¥7,930,000 (Direct Cost: ¥6,100,000、Indirect Cost: ¥1,830,000)
|
Keywords | 多重線形 / 腹部複数臓器 / スパース / Low-rank / 局所解析 / ボリューム / 医用画像 / テンプレートマッチング / 多重線形代数 / スパースコーディング / テンソル / 腹部CT / 複数臓器 / 統計モデリング / 主成分分析 / 医用画像データベース |
Outline of Final Research Achievements |
Recently, sparse coding is a hot topic for efficient data representation, and has been widely used in computer vision field. In this project, we proposed a generalized ND sparse coding based on multi-linear algebra, for direct analysis of multi-dimensional data without unfolding process. Experiments results on noise reduction demonstrated that the proposed method can achieve better results compared with the conventional sparse coding. We also proposed a framework for local morphological analysis (local statistical shape models) of 3D organs based on sparse and low rank matrix decomposition and applied our proposed method to computer-aided diagnostics of liver cirrhosis. The local abnormal regions can be detected by estimating the sparse components. The norm of the sparse components can be used as a measure for classification of the normal and abnormal livers. The classification accuracy by our proposed method is improved to 95%.
|
Report
(4 results)
Research Products
(89 results)
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[Journal Article] Quantification of Liver Shape on CT Using the Statistical Shape Model to Evaluate Hepatic Fibrosis2015
Author(s)
2.Masatoshi Hori, Toshiyuki Okada, Keisuke Higashiura, Yoshinobu Sato, Yen-Wei Chen, Tonsok Kim, Hiromitsu Onishi, Hidetoshi Eguchi, Hiroaki Nagano, Koji Umeshita, Kenichi Wakasa and Noriyuki Tomiyama
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Journal Title
Academic Radiology
Volume: Vol.22, No.3
Pages: 303-309
Related Report
Peer Reviewed / Open Access / Acknowledgement Compliant
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[Journal Article] Novel Liver Visualization and Surgical Simulation System2013
Author(s)
Kaibori M, Chen YW, Matsui K, Ishizaki M, Tsuda T, Nakatake R, Sakaguchi T, Matsushima H, Miyawaki K, Shindo T, Tateyama T, Kwon AH
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Journal Title
J Gastrointest Surg
Volume: Vol.17
Pages: 1422-1428
Related Report
Peer Reviewed
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[Journal Article] Enhanced Intestinal Motility during Oral Glucose Tolerance Test after Laparoscopic Sleeve Gastrectomy2013
Author(s)
Vo Nguyen Trung, Hiroshi Yamamoto1, Akira Furukawa, Tsuyoshi Yamaguchi, Satoshi Murata, Masahiro Yoshimura, Yoko Murakami, Shigetaka Sato, Hideji Otani, Satoshi Ugi, KatsutaroMorino, Hiroshi Maegawa, Tohru Tani
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Journal Title
Preliminary Results Using Cine Magnetic Resonance Imaging
Volume: Volume 8 | Issue 6 | e65739
Pages: 1-10
Related Report
Peer Reviewed
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[Journal Article] Design, synthesis, and preliminary ex vivo and in vivo evaluation of cationic magnetic resonance contrast agent for rabbit articular cartilage imaging.2013
Author(s)
Irie T, Oda K, Shiino A, Kubo M, Morikawa S, Urushiyama N, Aonuma S, Kimura T, Inubushi T, Oohashi T, Komatsu N.
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Journal Title
Med Chem Commun
Volume: 4
Issue: 11
Pages: 1508-1512
DOI
Related Report
Peer Reviewed
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[Book] Service Science and Data Mining2012
Author(s)
Chien-wen Shen, Sy-Yen 'Kuo, Kae Dal Kwack, Yen~Wei Chen, Ping-Yu Hsu and Franz Ko (Eds)
Publisher
Proceedings of 2012 International Conference on New Trends in Information Science
Related Report
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