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Paper Abstract and Keywords
Presentation 2015-05-15 13:30
Initial study of an automated recognition method of the supraspinatus muscle based on a muscle direction model in torso CT images
Tatsuya Katafuchi (Gifu Univ.), Naoki Kamiya (Aichi Pref. Univ.), Masanori Kume (Gifu Univ.), Xiangrong Zhou, Huayue Chen (Grad. Sch. Gifu Univ.), Asumi Kamiya (Higashi Nagoya Hosp.), Chisako Muramatsu, Takeshi Hara, Hiroshi Fujita (Grad. Sch. Gifu Univ.) SIP2015-22 IE2015-22 PRMU2015-22 MI2015-22
Abstract (in Japanese) (See Japanese page) 
(in English) The supraspinatus muscle is a functionally important muscle in four muscle groups that constitute the cuff. In this research, we propose an automatic recognition method of the supraspinatus muscle. We determine the muscular direction using the origin and insertion of the supraspinatus muscle, and construct the direction model. The proposed method is applied to eight normal adult CT cases. Recognition result in terms of the average concordance rate was 63.0%. The recognition was possible even in cases with individual variations. Therefore, it is considered that the method is effective for the automatic recognition of supraspinatus muscle. In the future, we will improve the segmentation accuracy of the supraspinatus muscle area by defining the precise skeleton area.
Keyword (in Japanese) (See Japanese page) 
(in English) Supraspinatus Muscle / CAD / Torso CT Image / Skeletal Muscle / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 25, MI2015-22, pp. 117-120, May 2015.
Paper # MI2015-22 
Date of Issue 2015-05-07 (SIP, IE, PRMU, MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SIP2015-22 IE2015-22 PRMU2015-22 MI2015-22

Conference Information
Committee PRMU MI IE SIP  
Conference Date 2015-05-14 - 2015-05-15 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2015-05-PRMU-MI-IE-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Initial study of an automated recognition method of the supraspinatus muscle based on a muscle direction model in torso CT images 
Sub Title (in English)  
Keyword(1) Supraspinatus Muscle  
Keyword(2) CAD  
Keyword(3) Torso CT Image  
Keyword(4) Skeletal Muscle  
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1st Author's Name Tatsuya Katafuchi  
1st Author's Affiliation Gifu University (Gifu Univ.)
2nd Author's Name Naoki Kamiya  
2nd Author's Affiliation Aichi Prefectural University (Aichi Pref. Univ.)
3rd Author's Name Masanori Kume  
3rd Author's Affiliation Gifu University (Gifu Univ.)
4th Author's Name Xiangrong Zhou  
4th Author's Affiliation Gifu University (Grad. Sch. Gifu Univ.)
5th Author's Name Huayue Chen  
5th Author's Affiliation Gifu University (Grad. Sch. Gifu Univ.)
6th Author's Name Asumi Kamiya  
6th Author's Affiliation National Hospital Organization, Higashi Nagoya National Hospital (Higashi Nagoya Hosp.)
7th Author's Name Chisako Muramatsu  
7th Author's Affiliation Gifu University (Grad. Sch. Gifu Univ.)
8th Author's Name Takeshi Hara  
8th Author's Affiliation Gifu University (Grad. Sch. Gifu Univ.)
9th Author's Name Hiroshi Fujita  
9th Author's Affiliation Gifu University (Grad. Sch. Gifu Univ.)
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Speaker Author-1 
Date Time 2015-05-15 13:30:00 
Presentation Time 30 minutes 
Registration for MI 
Paper # SIP2015-22, IE2015-22, PRMU2015-22, MI2015-22 
Volume (vol) vol.115 
Number (no) no.22(SIP), no.23(IE), no.24(PRMU), no.25(MI) 
Page pp.117-120 
#Pages
Date of Issue 2015-05-07 (SIP, IE, PRMU, MI) 


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