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Paper Abstract and Keywords
Presentation 2022-01-27 09:56
Segmentation of musculoskeletal structures in supine and upright CTs towards quantitative analysis of musculoskeletal deformation in standing position
Tomoki Hakotani, Yoshito Otake, Mazen Soufi (NAIST), Masahiro Hashimoto, Yoshitake Yamada, Minoru Yamada, Yoichi Yokoyama (Keio Univ.), Keisuke Uemura, Masaki Takao, Nobuhiko Sugano (Osaka Univ.), Masahiro Jinzaki (Keio Univ.), Yoshinobu Sato (NAIST) MI2021-70
Abstract (in Japanese) (See Japanese page) 
(in English) Musculoskeletal models that are faithful to medical images are important for clarifying the causes of movement disorders. Since the kinematic properties of the musculoskeletal system change depending on the body position, it is desirable to create a musculoskeletal model of standing movements based on medical images scanned in the standing position. However, medical images scanned in the upright position are less common than those in the supine position, and data are limited. Therefore, the final goal of our project is to quantify musculoskeletal deformation in the upright position and predict it from the images scanned in the supine position in order to effectively use images scanned in the supine position. In this study, as a first step, we automatically segmented supine and upright CT images scanned for the same subject, and determined the segmentation accuracy and the volume change with respect to the body position.
Keyword (in Japanese) (See Japanese page) 
(in English) upright CT / muscle segmentation / musculoskeletal deformation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 347, MI2021-70, pp. 106-110, Jan. 2022.
Paper # MI2021-70 
Date of Issue 2022-01-18 (MI) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee MI  
Conference Date 2022-01-25 - 2022-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2022-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Segmentation of musculoskeletal structures in supine and upright CTs towards quantitative analysis of musculoskeletal deformation in standing position 
Sub Title (in English)  
Keyword(1) upright CT  
Keyword(2) muscle segmentation  
Keyword(3) musculoskeletal deformation  
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1st Author's Name Tomoki Hakotani  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Yoshito Otake  
2nd Author's Affiliation Nara Institute of Science and Technology (NAIST)
3rd Author's Name Mazen Soufi  
3rd Author's Affiliation Nara Institute of Science and Technology (NAIST)
4th Author's Name Masahiro Hashimoto  
4th Author's Affiliation Keio University (Keio Univ.)
5th Author's Name Yoshitake Yamada  
5th Author's Affiliation Keio University (Keio Univ.)
6th Author's Name Minoru Yamada  
6th Author's Affiliation Keio University (Keio Univ.)
7th Author's Name Yoichi Yokoyama  
7th Author's Affiliation Keio University (Keio Univ.)
8th Author's Name Keisuke Uemura  
8th Author's Affiliation Osaka University (Osaka Univ.)
9th Author's Name Masaki Takao  
9th Author's Affiliation Osaka University (Osaka Univ.)
10th Author's Name Nobuhiko Sugano  
10th Author's Affiliation Osaka University (Osaka Univ.)
11th Author's Name Masahiro Jinzaki  
11th Author's Affiliation Keio University (Keio Univ.)
12th Author's Name Yoshinobu Sato  
12th Author's Affiliation Nara Institute of Science and Technology (NAIST)
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Speaker Author-1 
Date Time 2022-01-27 09:56:00 
Presentation Time 13 minutes 
Registration for MI 
Paper # MI2021-70 
Volume (vol) vol.121 
Number (no) no.347 
Page pp.106-110 
#Pages
Date of Issue 2022-01-18 (MI) 


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