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Paper Abstract and Keywords
Presentation 2022-11-18 14:25
Development of a Statistical Model for Predicting Aging Change in Spine and Pelvis Based on Landmarks Detected in a Large Scale Torso CT Image Database
Yuga Shimomoto, Yoshito Otake, Tomoki Hakotani, Mazen Soufi (NAIST), Hideki Shigematu (Nara Med. Univ.), Keisuke Uemura (Osaka Univ.), Masaki Takao (Ehime Univ.), Toshiaki Akashi (Juntendo Univ.), Kensaku Mori (Nagoya Univ./NII), Kento Aida (NII), Nobuhiko Sugano (Osaka Univ.), Yoshinobu Sato (NAIST) MICT2022-39 MI2022-68
Abstract (in Japanese) (See Japanese page) 
(in English) One way to describe variations in skeletal shape is a statistical shape model (SSM), which statistically analyzes organ shape data from multiple individuals. We aim to construct a SSM of the whole-body skeleton using a large CT database of more than 40,000 cases of J-MID collected by the Japan Radiological Society. As a first step, we extracted skeletal landmarks from a large CT image database of the torso (from the thoracic spine to the lower pelvis) and constructed SSM. Then, we investigated the age-related changes in skeletal shape and arrangement, and predicted the shape of the spine.
Keyword (in Japanese) (See Japanese page) 
(in English) statistical shape model / aging change analysis / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 265, MI2022-68, pp. 29-32, Nov. 2022.
Paper # MI2022-68 
Date of Issue 2022-11-11 (MICT, MI) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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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 MICT MI  
Conference Date 2022-11-18 - 2022-11-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Nagoya Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical imaging technology, healthcare and medical information communication technology, etc. 
Paper Information
Registration To MI 
Conference Code 2022-11-MICT-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development of a Statistical Model for Predicting Aging Change in Spine and Pelvis Based on Landmarks Detected in a Large Scale Torso CT Image Database 
Sub Title (in English)  
Keyword(1) statistical shape model  
Keyword(2) aging change analysis  
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1st Author's Name Yuga Shimomoto  
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 Tomoki Hakotani  
3rd Author's Affiliation Nara Institute of Science and Technology (NAIST)
4th Author's Name Mazen Soufi  
4th Author's Affiliation Nara Institute of Science and Technology (NAIST)
5th Author's Name Hideki Shigematu  
5th Author's Affiliation Nara Medical University (Nara Med. Univ.)
6th Author's Name Keisuke Uemura  
6th Author's Affiliation Osaka University (Osaka Univ.)
7th Author's Name Masaki Takao  
7th Author's Affiliation Ehime University (Ehime Univ.)
8th Author's Name Toshiaki Akashi  
8th Author's Affiliation Juntendo University (Juntendo Univ.)
9th Author's Name Kensaku Mori  
9th Author's Affiliation Nagoya University/National Institute of Informatics (Nagoya Univ./NII)
10th Author's Name Kento Aida  
10th Author's Affiliation National Institute of Informatics (NII)
11th Author's Name Nobuhiko Sugano  
11th Author's Affiliation Osaka University (Osaka 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 2022-11-18 14:25:00 
Presentation Time 25 minutes 
Registration for MI 
Paper # MICT2022-39, MI2022-68 
Volume (vol) vol.122 
Number (no) no.264(MICT), no.265(MI) 
Page pp.29-32 
#Pages
Date of Issue 2022-11-11 (MICT, MI) 


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