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Paper Abstract and Keywords
Presentation 2018-11-06 18:00
A Study of an Age Estimation Method From Brain MRI Images Using 3D-CNN and Its Application
Masaru Ueda, Koichi Ito (Tohoku Univ.), Kai Wu (South China Univ. of Tech.), Kazunori Sato, Yasuyuki Taki (Tohoku Univ.), Hiroshi Fukuda (Tohoku Medical and Pharmaceutical Univ.), Takafumi Aoki (Tohoku Univ.) MICT2018-57 MI2018-57
Abstract (in Japanese) (See Japanese page) 
(in English) The statistical analysis of brain MR images indicates that the human brain atrophies during normal aging process. The age of subjects can be estimated from brain images by modeling morphological changes. This model can be used to identify brain disorders by evaluating the actual and estimated age. This paper proposes an age estimation method from brain MRI images using 3D Convolutional Neural Network (3D-CNN). Through a set of experiments using T1-weighted images of patients with Alzheimer's disease, the proposed method exhibits the efficient performance on age estimation performance compared with conventional methods.
Keyword (in Japanese) (See Japanese page) 
(in English) MRI / T1-weighted image / age estimation / brain aging / deep learning / CNN / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 286, MI2018-57, pp. 79-82, Nov. 2018.
Paper # MI2018-57 
Date of Issue 2018-10-30 (MICT, MI) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 MICT2018-57 MI2018-57

Conference Information
Committee MICT MI  
Conference Date 2018-11-06 - 2018-11-06 
Place (in Japanese) (See Japanese page) 
Place (in English) University of Hyogo 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2018-11-MICT-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study of an Age Estimation Method From Brain MRI Images Using 3D-CNN and Its Application 
Sub Title (in English)  
Keyword(1) MRI  
Keyword(2) T1-weighted image  
Keyword(3) age estimation  
Keyword(4) brain aging  
Keyword(5) deep learning  
Keyword(6) CNN  
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Keyword(8)  
1st Author's Name Masaru Ueda  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Koichi Ito  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
3rd Author's Name Kai Wu  
3rd Author's Affiliation South China University of Technology (South China Univ. of Tech.)
4th Author's Name Kazunori Sato  
4th Author's Affiliation Tohoku University (Tohoku Univ.)
5th Author's Name Yasuyuki Taki  
5th Author's Affiliation Tohoku University (Tohoku Univ.)
6th Author's Name Hiroshi Fukuda  
6th Author's Affiliation Tohoku Medical and Pharmaceutical University (Tohoku Medical and Pharmaceutical Univ.)
7th Author's Name Takafumi Aoki  
7th Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2018-11-06 18:00:00 
Presentation Time 20 minutes 
Registration for MI 
Paper # MICT2018-57, MI2018-57 
Volume (vol) vol.118 
Number (no) no.285(MICT), no.286(MI) 
Page pp.79-82 
#Pages
Date of Issue 2018-10-30 (MICT, MI) 


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