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Paper Abstract and Keywords
Presentation 2018-07-24 14:35
Estimation of postmortem time for Ai-CT images by using Deep Learning
Shota Chai, Yasushi Hirano, Shoji Kido (Yamaguchi Univ.), Kazuyuki Kinoshita, Kunihiro Inai, Sakon Noriki (Univ. of Fukui) MI2018-28
Abstract (in Japanese) (See Japanese page) 
(in English) Although estimation of postmortem time is important for criminal investigation or sudden in-hospital death in the middle of the night, the accuracy of estimation is not high enough because the estimation is done by observation from the outside of the body and antemortem medical records in Japan. Furthermore the estimation depends on medical doctors' subjectivity and their experiences. In this study, we developed a method for estimating an objective and highly accurate postmortem time for Autopsy imaging (Ai) CT images. The method we developed extracted features by using autoencoder which is one of the Deep Learning techniques. As a result of the experiment, the mean absolute error between the actual and estimated postmortem time was 1.64 hours. It was shown that the proposed method had higher accuracy comparing with the method based on texture analysis.
Keyword (in Japanese) (See Japanese page) 
(in English) Ai-CT / Deep Learning / Estimation of postmortem time / Autopsy imaging / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 150, MI2018-28, pp. 33-37, July 2018.
Paper # MI2018-28 
Date of Issue 2018-07-17 (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 MI2018-28

Conference Information
Committee MI  
Conference Date 2018-07-24 - 2018-07-24 
Place (in Japanese) (See Japanese page) 
Place (in English) aiina (Morioka, Iwate) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2018-07-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Estimation of postmortem time for Ai-CT images by using Deep Learning 
Sub Title (in English)  
Keyword(1) Ai-CT  
Keyword(2) Deep Learning  
Keyword(3) Estimation of postmortem time  
Keyword(4) Autopsy imaging  
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1st Author's Name Shota Chai  
1st Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
2nd Author's Name Yasushi Hirano  
2nd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
3rd Author's Name Shoji Kido  
3rd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
4th Author's Name Kazuyuki Kinoshita  
4th Author's Affiliation University of Fukui (Univ. of Fukui)
5th Author's Name Kunihiro Inai  
5th Author's Affiliation University of Fukui (Univ. of Fukui)
6th Author's Name Sakon Noriki  
6th Author's Affiliation University of Fukui (Univ. of Fukui)
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Speaker Author-1 
Date Time 2018-07-24 14:35:00 
Presentation Time 20 minutes 
Registration for MI 
Paper # MI2018-28 
Volume (vol) vol.118 
Number (no) no.150 
Page pp.33-37 
#Pages 5 
Date of Issue 2018-07-17 (MI) 

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