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Paper Abstract and Keywords
Presentation 2021-05-17 15:10
[Short Paper] Fundamental study of automatic segmentation of skeletal muscle regions on whole body CT images based on a 3D DeepCNN
Kota Nozaki, Xiangong Zhou (Gifu Univ.), Naoki Kamiya (Aichi Prefectual Univ.), Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2021-7
Abstract (in Japanese) (See Japanese page) 
(in English) Amyotrophic lateral sclerosis (ALS) is an intractable disease in which voluntary muscles atrophy gradully due to degeneration of motor neurons. A definitive method for ALS diagnosis is required but it still has not been established. The quantitative information of skeletal muscle region such as volume and CT value that can be obtained from CT images may be useful for supporting ALS diagnosis. In this study, as a preliminary step to obtain quantitative information on skeletal muscles, we investigated an automatic method based on 3D Deep CNN for automatically segmatation surface skeletal muscle regions from whole-body CT images. The experimental results demonstrated that accuracies of the segmetanted skeletal muscle regions showed a mean value of 80.5% on Jaccard coefficient, and 88.8% on Dice coefficient by comapring to the human sketches on 21 whole body CT scans.
Keyword (in Japanese) (See Japanese page) 
(in English) Amyotrophic lateral sclerosis / whole-body CT image / skeletal muscle / 3D Deep CNN / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 21, MI2021-7, pp. 20-22, May 2021.
Paper # MI2021-7 
Date of Issue 2021-05-10 (MI) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 MI2021-7

Conference Information
Committee MI  
Conference Date 2021-05-17 - 2021-05-17 
Place (in Japanese) (See Japanese page) 
Place (in English) On-Line 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Image Processing, etc 
Paper Information
Registration To MI 
Conference Code 2021-05-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fundamental study of automatic segmentation of skeletal muscle regions on whole body CT images based on a 3D DeepCNN 
Sub Title (in English)  
Keyword(1) Amyotrophic lateral sclerosis  
Keyword(2) whole-body CT image  
Keyword(3) skeletal muscle  
Keyword(4) 3D Deep CNN  
1st Author's Name Kota Nozaki  
1st Author's Affiliation Gifu University (Gifu Univ.)
2nd Author's Name Xiangong Zhou  
2nd Author's Affiliation Gifu University (Gifu Univ.)
3rd Author's Name Naoki Kamiya  
3rd Author's Affiliation Aichi Prefectual University (Aichi Prefectual Univ.)
4th Author's Name Takeshi Hara  
4th Author's Affiliation Gifu University (Gifu Univ.)
5th Author's Name Hiroshi Fujita  
5th Author's Affiliation Gifu University (Gifu Univ.)
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Date Time 2021-05-17 15:10:00 
Presentation Time 30 
Registration for MI 
Paper # IEICE-MI2021-7 
Volume (vol) IEICE-121 
Number (no) no.21 
Page pp.20-22 
#Pages IEICE-3 
Date of Issue IEICE-MI-2021-05-10 

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