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Paper Abstract and Keywords
Presentation 2016-01-20 09:20
Preliminary study on automated recognition of iliopsoas muscle based on muscle direction model of psoas major and iliac muscle
Naoki Kamiya (Aichi Pref. Univ.), Xiangrong Zhou, Chisako Muramatsu, Takeshi Hara, Hiroki Kato (Gifu Univ.), Huayue Chen (Univ. of Occupational and Environmental Health), Ryujiro Yokoyama (Gifu Univ.), Huiyan Jiang (Northeastern Univ.), Masayuki Matsuo, Hiroshi Fujita (Gifu Univ.) MI2015-111
Abstract (in Japanese) (See Japanese page) 
(in English) We have proposed an automatic recognition method of skeletal muscle in CT images based on a shape model. We also proposed an automated recognition method of a psoas major muscle using shape model. We aim to recognize the iliacus muscle. The muscle fiber of iliacus muscle has characteristic direction. In this study, using 20 cases of training images, to obtain the approximate curve of iliacus muscle fiber. Specifically, the midpoint of a line connecting the origin and insertion, the distance value from the midpoint to the lobe of the iliacus muscle. Then, by calculating the ratio for this point and the origin (same as insertion and midpoint), to apply the test cases. In the recognition process, using curved surface generated by the approximated curve as a mask. The recognition result in five cases with no abnormality in skeletal muscle, obtained 76.9 % average concordance rate. Therefore, it is considered that the proposed method is effective for the recognition of the initial region of iliacus muscle with highly accuracy. In the future, we will integrate the recognition method of psoas major muscle, to develop the analytical technique of iliopsoas area. Furthermore, it is necessary to sophisticated to muscle function analysis.
Keyword (in Japanese) (See Japanese page) 
(in English) Iliacus muscle / CAD / Torso CT image / Skeletal muscle / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 401, MI2015-111, pp. 183-186, Jan. 2016.
Paper # MI2015-111 
Date of Issue 2016-01-12 (MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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Conference Information
Committee MI  
Conference Date 2016-01-19 - 2016-01-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunka Tenbusu Kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General topics in medical imaging 
Paper Information
Registration To MI 
Conference Code 2016-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Preliminary study on automated recognition of iliopsoas muscle based on muscle direction model of psoas major and iliac muscle 
Sub Title (in English)  
Keyword(1) Iliacus muscle  
Keyword(2) CAD  
Keyword(3) Torso CT image  
Keyword(4) Skeletal muscle  
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1st Author's Name Naoki Kamiya  
1st Author's Affiliation Aichi Prefectural University (Aichi Pref. Univ.)
2nd Author's Name Xiangrong Zhou  
2nd Author's Affiliation Gifu University (Gifu Univ.)
3rd Author's Name Chisako Muramatsu  
3rd Author's Affiliation Gifu University (Gifu Univ.)
4th Author's Name Takeshi Hara  
4th Author's Affiliation Gifu University (Gifu Univ.)
5th Author's Name Hiroki Kato  
5th Author's Affiliation Gifu University (Gifu Univ.)
6th Author's Name Huayue Chen  
6th Author's Affiliation University of Occupational and Environmental Health (Univ. of Occupational and Environmental Health)
7th Author's Name Ryujiro Yokoyama  
7th Author's Affiliation Gifu University (Gifu Univ.)
8th Author's Name Huiyan Jiang  
8th Author's Affiliation Northeastern University (Northeastern Univ.)
9th Author's Name Masayuki Matsuo  
9th Author's Affiliation Gifu University (Gifu Univ.)
10th Author's Name Hiroshi Fujita  
10th Author's Affiliation Gifu University (Gifu Univ.)
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Speaker Author-1 
Date Time 2016-01-20 09:20:00 
Presentation Time 12 minutes 
Registration for MI 
Paper # MI2015-111 
Volume (vol) vol.115 
Number (no) no.401 
Page pp.183-186 
#Pages
Date of Issue 2016-01-12 (MI) 


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