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Paper Abstract and Keywords
Presentation 2013-01-25 10:50
Automated recognition of the rectus abdominis muscle in CT images based on a virtual image-unfolding technique by the removal of the subcutaneous fat region
Naoki Kamiya (Toyota Nat'l Col. Tech.), Chisako Muramatsu, Xiangrong Zhou, Huayue Chen, Takeshi Hara, Hiroaki Hoshi, Hiroshi Fujita (Gifu Univ.) MI2012-99
Abstract (in Japanese) (See Japanese page) 
(in English) We had proposed an automated method for recognizing skeletal muscle in torso X-ray CT images using skeletal positional information and shape model of its muscle, and confirmed that the method was effective in recognizing the muscles. The previous method recognized the muscle’s connecting points on the virtually unfolded image of the human body as landmarks and fitted a shape model based on the positional information obtained from the landmarks, to recognize the muscle region automatically. However, there was a variation in recognition accuracy at the site where the surface shape is greatly different depending on the difference in physique such as an abdominal region. In this paper, we have improved the virtual image-unfolding technique. The proposed method removed the subcutaneous fat area beforehand because of its significant difference by physique between patients, and applied the remaining regions for recognition of the muscle. We applied this methodology to 10 patients with no evidence of abnormalities to the rectus abdominis muscle. We achieved the 89% concordance with manual segmentation and confirmed the effectiveness of the muscle polyventer shape modeling and recognition.
Keyword (in Japanese) (See Japanese page) 
(in English) CAD / X-ray CT images / skeletal muscle / rectus abdominis muscle / / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 411, MI2012-99, pp. 197-200, Jan. 2013.
Paper # MI2012-99 
Date of Issue 2013-01-17 (MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 2013-01-24 - 2013-01-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunka Tenbusu Kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Computational anatomy and its application to computer assisted diagnosis and therapy, etc 
Paper Information
Registration To MI 
Conference Code 2013-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automated recognition of the rectus abdominis muscle in CT images based on a virtual image-unfolding technique by the removal of the subcutaneous fat region 
Sub Title (in English)  
Keyword(1) CAD  
Keyword(2) X-ray CT images  
Keyword(3) skeletal muscle  
Keyword(4) rectus abdominis muscle  
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1st Author's Name Naoki Kamiya  
1st Author's Affiliation Toyota National College of Technology (Toyota Nat'l Col. Tech.)
2nd Author's Name Chisako Muramatsu  
2nd Author's Affiliation Gifu University (Gifu Univ.)
3rd Author's Name Xiangrong Zhou  
3rd Author's Affiliation Gifu University (Gifu Univ.)
4th Author's Name Huayue Chen  
4th Author's Affiliation Gifu University (Gifu Univ.)
5th Author's Name Takeshi Hara  
5th Author's Affiliation Gifu University (Gifu Univ.)
6th Author's Name Hiroaki Hoshi  
6th Author's Affiliation Gifu University (Gifu Univ.)
7th Author's Name Hiroshi Fujita  
7th Author's Affiliation Gifu University (Gifu Univ.)
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Speaker Author-1 
Date Time 2013-01-25 10:50:00 
Presentation Time 15 minutes 
Registration for MI 
Paper # MI2012-99 
Volume (vol) vol.112 
Number (no) no.411 
Page pp.197-200 
#Pages
Date of Issue 2013-01-17 (MI) 


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