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Paper Abstract and Keywords
Presentation 2014-01-26 13:30
Model-based approach to recognize the middle and inferior fibers of the trapezius muscle in torso CT images
Haruka Kobayashi, Naoki Kamiya (Toyota Nat'l Col. Tech.), Asumi Kamiya (Higashi Nagoya National Hospital), Xiangrong Zhou, Huayue Chen, Chisako Muramatsu, Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2013-68
Abstract (in Japanese) (See Japanese page) 
(in English) We have proposed an automatic recognition method of skeletal muscle in torso CT images based on a shape model and positional information of the skeleton. We also proposed a construction method of a virtually unfolded image. In the virtually unfolded image, since the complex human body shape can be expressed simply, the recognition of the rectus abdominis muscle is realized in the abdomen region. In this study, we validate the recognition technique of the skeletal muscle using virtual unfolding technique in surface muscle. We aim to recognize the trapezius muscle which is located in the back surface where automated recognition has not yet been realized. It is believed that the recognition of the trapezius muscle will help the site specific analysis of muscle, such as in the analysis of the impact of Visual Display Terminals work to the trapezius muscle and muscle hypertrophy due to neck falling in Parkinson’s disease. The result of the recognition in six cases with no abnormality in skeletal muscle, obtained 91.6 % average concordance rate. Therefore, it is considered that the trapezius muscle recognition can be possible at a relatively high concordance rate, and the proposed method is effective for recognition of the surface muscle.
Keyword (in Japanese) (See Japanese page) 
(in English) CAD / X-ray CT images / skeletal muscle / trapezius muscle / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 410, MI2013-68, pp. 69-72, Jan. 2014.
Paper # MI2013-68 
Date of Issue 2014-01-19 (MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 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)
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Conference Information
Committee MI  
Conference Date 2014-01-26 - 2014-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunka Tenbusu Kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Computer Assisted Diagnosis and Therapy Based on Computational Anatomy, etc. 
Paper Information
Registration To MI 
Conference Code 2014-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Model-based approach to recognize the middle and inferior fibers of the trapezius muscle in torso CT images 
Sub Title (in English)  
Keyword(1) CAD  
Keyword(2) X-ray CT images  
Keyword(3) skeletal muscle  
Keyword(4) trapezius muscle  
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1st Author's Name Haruka Kobayashi  
1st Author's Affiliation Toyota National College of Technology (Toyota Nat'l Col. Tech.)
2nd Author's Name Naoki Kamiya  
2nd Author's Affiliation Toyota National College of Technology (Toyota Nat'l Col. Tech.)
3rd Author's Name Asumi Kamiya  
3rd Author's Affiliation Higashi Nagoya National Hospital (Higashi Nagoya National Hospital)
4th Author's Name Xiangrong Zhou  
4th Author's Affiliation Gifu University (Gifu Univ.)
5th Author's Name Huayue Chen  
5th Author's Affiliation Gifu University (Gifu Univ.)
6th Author's Name Chisako Muramatsu  
6th Author's Affiliation Gifu University (Gifu Univ.)
7th Author's Name Takeshi Hara  
7th Author's Affiliation Gifu University (Gifu Univ.)
8th Author's Name Hiroshi Fujita  
8th Author's Affiliation Gifu University (Gifu Univ.)
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Speaker Author-1 
Date Time 2014-01-26 13:30:00 
Presentation Time 45 minutes 
Registration for MI 
Paper # MI2013-68 
Volume (vol) vol.113 
Number (no) no.410 
Page pp.69-72 
#Pages 4 
Date of Issue 2014-01-19 (MI) 

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