Advancement of iliopsoas muscle analysis by development of 3D image analysis technique of iliac muscle

• Project/Area Number: 15K21588
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Medical Physics and Radiological Technology; Medical systems
• Research Institution: Aichi Prefectural University
• Principal Investigator: KAMIYA Naoki 愛知県立大学, 情報科学部, 講師 (00580945)
• Research Collaborator: FUJITA Hiroshi ; HARA Takeshi ; ZHOU Xiangrong ; MURAMATSU Chisako ; CHEN Huayue ; IEDA Kosuke
• Project Period (FY): 2015-04-01 – 2018-03-31
• Project Status: Completed (Fiscal Year 2017)
• Budget Amount: ¥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)
• 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.

Research Products

• [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
  • Journal Title: Proceedings of the Fourth International Symposium on the Project "Multidisciplinary Computational Anatomy" Volume: - Pages: 115-124
• [Journal Article] Segmental recognition of skeletal muscle in whole-body CT images and its texture analysis using skeletal muscle models (2017)
  • 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
  • Journal Title: Proceedings of International Journal of Computer Assisted Radiology and Surgery Volume: 12 Pages: 275-275
• [Journal Article] Automated analysis of whole skeletal muscle for muscular atrophy detection of ALS in whole-body CT images: preliminary study (2017)
  • 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
  • Journal Title: Proceedings of SPIE Medical Imaging 2017, Computer-Aided Diagnosis Volume: 10134 Pages: 1013442-1013442
  • DOI: 10.1117/12.2251584
  • Peer Reviewed / Acknowledgement Compliant
• [Journal Article] Automated recognition of the iliac muscle and modeling of muscle fiber direction in torso CT images (2016)
  • Author(s): N. Kamiya, X. Zhou, K. Azuma, C. Muramatsu, T. Hara and H. Fujita
  • Journal Title: Proc. SPIE Medical Imaging 2016: Computer-Aided Diagnosis Volume: 9785
  • DOI: 10.1117/12.2214613
  • Peer Reviewed / Acknowledgement Compliant
• [Presentation] 全身CT画像における腸腰筋モデルを用いたテクスチャ解析に基づくALSの自動鑑別の初期検討 (2017)
  • Author(s): 神谷直希，家田皓将，周 向栄，山田 恵，加藤博基，東 華岳，村松千左子，原 武史，三好利治，犬塚 貴，松尾正之，藤田広志
  • Organizer: 電子情報通信学会技術研究報告(MI2016-86)(2017-01)
  • Place of Presentation: 沖縄県那覇市ぶんかテンブス館
  • Year and Date: 2017-01-18
• [Presentation] Segmental recognition of skeletal muscle in whole-body CT images and its texture analysis using skeletal muscle models (2017)
  • 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
  • Int'l Joint Research
• [Presentation] 全身CT 画像における3D テクスチャ解析によるALS 群と筋原性・神経原性疾患群の画像特徴解析 (2017)
  • Author(s): 淺野瑛里香，神谷直希，周向栄，山田恵，加藤博基，村松千左子，原武史，三好利治，松尾政之，藤田広志
  • Organizer: 平成29年度日本生体医工学会東海支部学術集会
• [Presentation] Composite recognition of the iliopsoas muscle based on the muscle direction modeling in CT images (2016)
  • Author(s): N. Kamiya, X. Zhou, H. Kato, K. Azuma, C. Muramatsu, T. Hara and H. Fujita
  • Organizer: 18th International Workshop on Computer-Aided Diagnosis, Special Session: Hot Topics in CAD
  • Place of Presentation: Heidelberg Convention Center, Germany
  • Year and Date: 2016-06-23
  • Int'l Joint Research / Invited
• [Presentation] Automated Analysis of Intramuscular Fat Tissue in the Lower Limbs with a Case of Amyotrophic Lateral Sclerosis (ALS) in Whole-body CT Images (2016)
  • Author(s): N. Kamiya, K. Ieda, X. Zhou, M. Yamada, C. Muramatsu, T. Hara and H. Fujita
  • Organizer: 日本放射線技術学会 第72回総会学術大会予稿集
  • Place of Presentation: パシフィコ横浜会議センター
  • Year and Date: 2016-04-14
• [Presentation] 大腰筋と腸骨筋の筋走行モデルに基づく腸腰筋認識の初期検討 (2016)
  • Author(s): 神谷直希，周 向栄，村松千左子，原 武史，加藤博基，東 華岳，横山龍二郎，姜 慧研，松尾政之，藤田広志
  • Organizer: 電子情報通信学会技術研究報告(MI2015-111)
  • Place of Presentation: 沖縄県那覇市ぶんかテンブス館
  • Year and Date: 2016-01-19
• [Presentation] Composite recognition of the iliopsoas muscle based on the muscle direction modeling in CT images (2016)
  • Author(s): N. Kamiya, H. Kato, X. Zhou, C. Muramatsu, T. Hara, H. Fujita and H. Chen
  • Organizer: International Workshop on Advanced Image Technology 2016
  • Place of Presentation: Pukyong University, BUSAN, KOREA
  • Year and Date: 2016-01-06
  • Int'l Joint Research / Invited
• [Book] Understanding Medical Images Based on Computational Anatomy Models (2017)
  • Author(s): S. Hanaoka, N. Kamiya, Y. Sato et.al.
  • Total Pages: 284
  • Publisher: Springer Japan
• [Remarks] 愛知県立大学情報科学部神谷直希研究室
  • URL: http://www.ist.aichi-pu.ac.jp/~n-kamiya