Paper Abstract and Keywords |
Presentation |
2018-03-19 10:05
A preliminary study on unsupervised registration with deep learning Kai Nagara, Holger R. Roth, Shota Nakamura, Masahiro Oda, Kensaku Mori (Nagoya Univ.) MI2017-65 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Registration is one of the important processes in medical image processing. Many researchers have proposed methods for registration. However, few learning-based non-rigid registration method has developed because of the difficulty of preparing a lot of ground truth data for non-rigid registration. To solve this problem, a registration method by using unsupervised deep learning has been proposed. In the registration method by unsupervised learning, it is not necessary to create ground truth data. However, in this method, the network cannot learn the global structures because the range of convolution is limited. Therefore, in this paper, we propose a network introducing a coarse-to-fine approach to learn global structures. The proposed network consists of multiple networks with pooling layers having different kernel sizes. Moreover, we develop a loss function that combines outputs from these multiple networks. The proposed network outputs deformed images according to the reference images. Experimental results using the proposed method showed better registration results than conventional methods. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep learning / Unsupervised learning / Non-rigid registration / Micro CT / HE stained image / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 518, MI2017-65, pp. 7-12, March 2018. |
Paper # |
MI2017-65 |
Date of Issue |
2018-03-12 (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) |
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MI2017-65 |
Conference Information |
Committee |
SIP EA SP MI |
Conference Date |
2018-03-19 - 2018-03-20 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
|
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] |
Paper Information |
Registration To |
MI |
Conference Code |
2018-03-SIP-EA-SP-MI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A preliminary study on unsupervised registration with deep learning |
Sub Title (in English) |
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Keyword(1) |
Deep learning |
Keyword(2) |
Unsupervised learning |
Keyword(3) |
Non-rigid registration |
Keyword(4) |
Micro CT |
Keyword(5) |
HE stained image |
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1st Author's Name |
Kai Nagara |
1st Author's Affiliation |
Nagoya University (Nagoya Univ.) |
2nd Author's Name |
Holger R. Roth |
2nd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
3rd Author's Name |
Shota Nakamura |
3rd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
4th Author's Name |
Masahiro Oda |
4th Author's Affiliation |
Nagoya University (Nagoya Univ.) |
5th Author's Name |
Kensaku Mori |
5th Author's Affiliation |
Nagoya University (Nagoya Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-03-19 10:05:00 |
Presentation Time |
15 minutes |
Registration for |
MI |
Paper # |
MI2017-65 |
Volume (vol) |
vol.117 |
Number (no) |
no.518 |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2018-03-12 (MI) |
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