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Paper Abstract and Keywords
Presentation 2015-03-02 16:12
Imaging position recognition of CT images using deep learning for computational medical image understanding.
Fumiyasu Noshiro, Masahito Aoyama, Yoshitaka Masutani (Hiroshima City Univ.) MI2014-84
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we describe our method based on deep learning and majority voting for imaging position recognition, which can be the first step of computational medical image understanding. The problem is classification of 4 classes of positions; head, chest, abdomen, and pelvis for axial sections of X-ray CT images. To collect large quantities of various training data, we used keyword search on the internet. First, in our method, small patches randomly extracted from training data sets are used for training convolutional neural network. Next, small patches are extracted from test image in the similar way and individual classification results are obtained for the patches. Finally, majority voting is performed for obtaining the final classification result. In the experiment by using 724 training images and 361 test images, we obtained 94% of classification accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) CT image / medical image understanding / deep learning / majority voting / imaging position recognition / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 482, MI2014-84, pp. 143-146, March 2015.
Paper # MI2014-84 
Date of Issue 2015-02-23 (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 MI2014-84

Conference Information
Committee MI  
Conference Date 2015-03-02 - 2015-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Hotel Miyahira 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Creation of multidisciplinary computational anatomy, Forefront of medical image engineering, General topics in medical imaging 
Paper Information
Registration To MI 
Conference Code 2015-03-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Imaging position recognition of CT images using deep learning for computational medical image understanding. 
Sub Title (in English)  
Keyword(1) CT image  
Keyword(2) medical image understanding  
Keyword(3) deep learning  
Keyword(4) majority voting  
Keyword(5) imaging position recognition  
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1st Author's Name Fumiyasu Noshiro  
1st Author's Affiliation Hirosihma City University (Hiroshima City Univ.)
2nd Author's Name Masahito Aoyama  
2nd Author's Affiliation Hirosihma City University (Hiroshima City Univ.)
3rd Author's Name Yoshitaka Masutani  
3rd Author's Affiliation Hirosihma City University (Hiroshima City Univ.)
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Speaker Author-1 
Date Time 2015-03-02 16:12:00 
Presentation Time 12 minutes 
Registration for MI 
Paper # MI2014-84 
Volume (vol) vol.114 
Number (no) no.482 
Page pp.143-146 
#Pages 4 
Date of Issue 2015-02-23 (MI) 

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