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Paper Abstract and Keywords
Presentation 2026-03-06 16:32
Development of a Method for Predicting Musculoskeletal Geometry from Optical 3D Body Surface Scan Data Using a Statistical Shape Model
Ryota Suzuki, Yi Gu, Mazen Soufi (NAIST), Kaoru Fujihara, Yoji Katsuhara (HSRC), Yoshitake Yamada, Masahiro Jinzaki (Keio), Sato Yoshinobu, Yoshito Otake (NAIST) MI2025-116
Abstract (in Japanese) (See Japanese page) 
(in English) Quantitative assessment of muscle mass is important for the early detection of age-related diseases such as sarcopenia; however, CT and MRI are not suitable for large-scale screening because of radiation exposure and cost. In this study, we propose a method for estimating internal musculoskeletal structures from three-dimensional body surface scan data that can be acquired noninvasively and within a short time. First, a statistical shape model integrating body surface and musculoskeletal geometries was constructed from lower-limb CT images. Next, for the lower-limb region extracted from whole-body surface scan data, the shape weights were optimized using only the body surface data and the principal component vectors corresponding to the surface, enabling reconstruction of the body surface shape while simultaneously estimating the musculoskeletal structure. Experimental results showed that estimated shapes were similar among subjects with similar physiques, whereas corresponding differences were observed among subjects with large physique differences, indicating that the proposed method can reflect physique-dependent morphological variations to a certain extent.
Keyword (in Japanese) (See Japanese page) 
(in English) Statistical Shape Model / Non-rigid Registration / Quasi-Newton method / L-BFGS-B / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 395, MI2025-116, pp. 207-210, March 2026.
Paper # MI2025-116 
Date of Issue 2026-02-26 (MI) 
ISSN 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)
Download PDF MI2025-116

Conference Information
Committee MI  
Conference Date 2026-03-05 - 2026-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) OKINAWAKEN SEINENKAIKAN 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2026-03-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development of a Method for Predicting Musculoskeletal Geometry from Optical 3D Body Surface Scan Data Using a Statistical Shape Model 
Sub Title (in English)  
Keyword(1) Statistical Shape Model  
Keyword(2) Non-rigid Registration  
Keyword(3) Quasi-Newton method  
Keyword(4) L-BFGS-B  
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1st Author's Name Ryota Suzuki  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Yi Gu  
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 Kaoru Fujihara  
4th Author's Affiliation Wacoal Human Science Research & Development Center (HSRC)
5th Author's Name Yoji Katsuhara  
5th Author's Affiliation Wacoal Human Science Research & Development Center (HSRC)
6th Author's Name Yoshitake Yamada  
6th Author's Affiliation Keio University (Keio)
7th Author's Name Masahiro Jinzaki  
7th Author's Affiliation Keio University (Keio)
8th Author's Name Sato Yoshinobu  
8th Author's Affiliation Nara Institute of Science and Technology (NAIST)
9th Author's Name Yoshito Otake  
9th Author's Affiliation Nara Institute of Science and Technology (NAIST)
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Speaker Author-1 
Date Time 2026-03-06 16:32:00 
Presentation Time 13 minutes 
Registration for MI 
Paper # MI2025-116 
Volume (vol) vol.125 
Number (no) no.395 
Page pp.207-210 
#Pages 4 
Date of Issue 2026-02-26 (MI) 

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