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Paper Abstract and Keywords
Presentation 2016-01-20 14:26
Estimation of Liver Deformation Using Real-Time Nonlinear Finite Element Method by Deep Neural Network
Kaoru Kobayashi, Ken'ichi Morooka (Kyushu Univ.), Yasushi Miyagi (Kaizuka Hospital), Takaichi Fukuda (Kumamoto Univ.), Tokuo Tsuji, Ryo Kurazume (Kyushu Univ.), Kazuhiro Samura (Fukuoka Univ.) MI2015-138
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a real-time nonlinear nite element method (FEM) for estimating soft tissue deformations by deep neural network (NN). When the volume model of a target human tissue is given, FE analysis simulates the behaviors of the tissue by using the displacement and force of each node in the volume model. Considering the analysis, one NN for each node is constructed by a large number of the deformation patterns derived from FE analysis. The proposed system consists of the large scale deep NN integrated by the networks of all the
nodes. From our experiments, our method can predict the reliable behavior of the node in real-time.
Keyword (in Japanese) (See Japanese page) 
(in English) Soft tissue deformation / Nonlinear deformation / Finite element method / Deep learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 401, MI2015-138, pp. 321-325, Jan. 2016.
Paper # MI2015-138 
Date of Issue 2016-01-12 (MI) 
ISSN Print edition: ISSN 0913-5685    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 MI2015-138

Conference Information
Committee MI  
Conference Date 2016-01-19 - 2016-01-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunka Tenbusu Kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General topics in medical imaging 
Paper Information
Registration To MI 
Conference Code 2016-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Estimation of Liver Deformation Using Real-Time Nonlinear Finite Element Method by Deep Neural Network 
Sub Title (in English)  
Keyword(1) Soft tissue deformation  
Keyword(2) Nonlinear deformation  
Keyword(3) Finite element method  
Keyword(4) Deep learning  
Keyword(5)  
Keyword(6)  
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1st Author's Name Kaoru Kobayashi  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Ken'ichi Morooka  
2nd Author's Affiliation Kyushu University (Kyushu Univ.)
3rd Author's Name Yasushi Miyagi  
3rd Author's Affiliation Kaizuka Hospital (Kaizuka Hospital)
4th Author's Name Takaichi Fukuda  
4th Author's Affiliation Kumamoto University (Kumamoto Univ.)
5th Author's Name Tokuo Tsuji  
5th Author's Affiliation Kyushu University (Kyushu Univ.)
6th Author's Name Ryo Kurazume  
6th Author's Affiliation Kyushu University (Kyushu Univ.)
7th Author's Name Kazuhiro Samura  
7th Author's Affiliation Fukuoka University (Fukuoka Univ.)
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Speaker Author-1 
Date Time 2016-01-20 14:26:00 
Presentation Time 12 minutes 
Registration for MI 
Paper # MI2015-138 
Volume (vol) vol.115 
Number (no) no.401 
Page pp.321-325 
#Pages 5 
Date of Issue 2016-01-12 (MI) 

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