Advancement of iliopsoas muscle analysis by development of 3D image analysis technique of iliac muscle
Project/Area Number |
15K21588
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Medical Physics and Radiological Technology
Medical systems
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Research Institution | Aichi Prefectural University |
Principal Investigator |
KAMIYA Naoki 愛知県立大学, 情報科学部, 講師 (00580945)
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Research Collaborator |
FUJITA Hiroshi
HARA Takeshi
ZHOU Xiangrong
MURAMATSU Chisako
CHEN Huayue
IEDA Kosuke
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Project Period (FY) |
2015-04-01 – 2018-03-31
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Project Status |
Completed (Fiscal Year 2017)
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Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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Keywords | 腸腰筋 / 腸骨筋 / 大腰筋 / 筋走行モデリング / 骨格筋自動認識 / 骨格筋自動解析 / 骨格筋複合モデル / 腸腰筋認識 / 腸骨筋認識 / 大腰筋認識 / 骨格筋形状モデリング |
Outline of Final Research Achievements |
In this research, we focused on the iliopsoas muscles, which are the muscles related to the autonomous walking function. We achieved automatic recognition of the iliac muscle constituting the iliopsoas muscle and development of three dimensional automatic analysis technique of the iliopsoas muscle combined with the psoas major and iliac muscle. Here, in addition to a shape model representing the outline of the large psoas muscle developed by our previous study, we also constructed a shape model of the iliac muscle. In order to apply this shape model to arbitrary cases, we first calculate the landmarks as feature points from the anatomical origin and insertion, then, in the muscle fiber direction model modeling the direction of the muscles between the landmarks. Finally, a shape model was fitted on the muscle fiber running model to realize recognition. Furthermore, we developed a technique to analyze recognized skeletal muscles not only by muscle mass but also by texture features.
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Report
(4 results)
Research Products
(13 results)
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[Journal Article] Function Integrated Diagnostic Assistance Based on Multidisciplinary Computational Anatomy Models" -Progress Overview FY2017-2018
Author(s)
H. Fujita, T. Hara, X. Zhou, K. Azuma, D. Fukuoka, Y. Hatanaka, N. Kamiya, T. Katafuchi, T. Matsubara, M. Matsuo, T. Miyati, C. Muramatsu, A. Teramoto and Y. Uchiyama
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Journal Title
Proceedings of the Fourth International Symposium on the Project "Multidisciplinary Computational Anatomy"
Volume: -
Pages: 115-124
Related Report
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[Journal Article] Segmental recognition of skeletal muscle in whole-body CT images and its texture analysis using skeletal muscle models2017
Author(s)
N. Kamiya, E. Asano, X. Zhou, M. Yamada, H. Kato, K. Azuma, C. Muramatsu, T. Hara, T. Miyoshi, T. Inuzuka, M. Matsuo and H. Fujita
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Journal Title
Proceedings of International Journal of Computer Assisted Radiology and Surgery
Volume: 12
Pages: 275-275
Related Report
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[Journal Article] Automated analysis of whole skeletal muscle for muscular atrophy detection of ALS in whole-body CT images: preliminary study2017
Author(s)
N.Kamiya, K.Ieda, X.Zhou, M.Yamada, H.Kato, C.Muramatsu, T.Hara, T.Miyoshi, T.Inuzuka, M.Matsuo, and H.Fujita
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Journal Title
Proc. SPIE Medical Imaging 2017: Computer-Aided Diagnosis
Volume: 10134
Pages: 1013442-1013442
DOI
Related Report
Peer Reviewed
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[Presentation] Segmental recognition of skeletal muscle in whole-body CT images and its texture analysis using skeletal muscle models2017
Author(s)
N. Kamiya, E. Asano, X. Zhou, M. Yamada, H. Kato, K. Azuma, C. Muramatsu, T. Hara, T. Miyoshi, T. Inuzuka, M. Matsuo and H. Fujita
Organizer
Computer Assisted Radiology and Surgery
Related Report
Int'l Joint Research
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