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Paper Abstract and Keywords
Presentation 2017-07-06 16:15
An Automated Method for Generating Training Data for Image Registration Using Deep Learning
Masato Ito, Fumihiko Ino, Kenichi Hagihara (Osaka Univ.) MI2017-28
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose an automated method for generating training data that realizes image registration with deep learning. The proposed method minimizes efforts required for supervised learning by automatically generating millions of training sets from tens of vector fields obtained with actual registration. To automate this procedure, we produce a floating image by applying a vector field $Phi$ to a reference image and obtain the vector field for these images from the inverse vector of $Phi$. In experiments, the proposed method took 33 minutes to produce approximately 170,000 training sets from approximately 670,000 2-D magnetic resonance (MR) images and 30 vector fields generated with a previous registration method. We further trained GoogLeNet with these training sets and performed holdout validation to compare the proposed method with the previous registration method in terms of recall and precision. As a result, the proposed method increased recall and precision from 50% to 80%, predicting deformation vectors more correctly.
Keyword (in Japanese) (See Japanese page) 
(in English) Image registration / nonrigid registration / deep learning / training data / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 117, MI2017-28, pp. 11-16, July 2017.
Paper # MI2017-28 
Date of Issue 2017-06-29 (MI) 
ISSN Print edition: ISSN 0913-5685    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)
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Conference Information
Committee MI  
Conference Date 2017-07-06 - 2017-07-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2017-07-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Automated Method for Generating Training Data for Image Registration Using Deep Learning 
Sub Title (in English)  
Keyword(1) Image registration  
Keyword(2) nonrigid registration  
Keyword(3) deep learning  
Keyword(4) training data  
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1st Author's Name Masato Ito  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Fumihiko Ino  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Kenichi Hagihara  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2017-07-06 16:15:00 
Presentation Time 30 minutes 
Registration for MI 
Paper # MI2017-28 
Volume (vol) vol.117 
Number (no) no.117 
Page pp.11-16 
#Pages
Date of Issue 2017-06-29 (MI) 


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