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Paper Abstract and Keywords
Presentation 2014-01-26 14:25
[Special Talk] Development of similar case retrieval technology for supporting medical image diagnosis and education of various lung diseases
Kazuki Kozuka, Kazutoyo Takata, Kenji Kondo, Masaki Kiyono (Panasonic), Masato Tanaka, Toyohiko Sakai, Hirohiko Kimura (Univ. of Fukui) MI2013-81
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a new CBIR(Content-based Image Retrieval) system that can retrieve similar cases include “diffusive lung diseases” as well as pulmonary nodules. Because there are many types of lung diseases, CBIR systems require many kinds of image features. However, in a system using image features only, the queries cannot reflect the grounds of doctors’ decisions. Such systems cannot retrieve similar images that the doctor really wants to consult. Therefore, we also propose a new retrieval method that can reflect doctors’ attention by analyzing finding expressions. This method extracts radiological knowledge from database of clinical cases beforehand. When a doctor searches similar cases, the system dynamically changes weights for image features by using findings specified by a doctor. The proposed method was evaluated in experiments with 1026 cases of lung diseases, and the experimental results showed that proposed method improved the accuracy of image retrieval compared with the conventional method.
Keyword (in Japanese) (See Japanese page) 
(in English) Content-based image-retrieval system / Chest computed tomography / Case database / / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 410, MI2013-81, pp. 139-142, Jan. 2014.
Paper # MI2013-81 
Date of Issue 2014-01-19 (MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 2014-01-26 - 2014-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunka Tenbusu Kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Computer Assisted Diagnosis and Therapy Based on Computational Anatomy, etc. 
Paper Information
Registration To MI 
Conference Code 2014-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development of similar case retrieval technology for supporting medical image diagnosis and education of various lung diseases 
Sub Title (in English)  
Keyword(1) Content-based image-retrieval system  
Keyword(2) Chest computed tomography  
Keyword(3) Case database  
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1st Author's Name Kazuki Kozuka  
1st Author's Affiliation Panasonic Corporation (Panasonic)
2nd Author's Name Kazutoyo Takata  
2nd Author's Affiliation Panasonic Corporation (Panasonic)
3rd Author's Name Kenji Kondo  
3rd Author's Affiliation Panasonic Corporation (Panasonic)
4th Author's Name Masaki Kiyono  
4th Author's Affiliation Panasonic Corporation (Panasonic)
5th Author's Name Masato Tanaka  
5th Author's Affiliation University of Fukui (Univ. of Fukui)
6th Author's Name Toyohiko Sakai  
6th Author's Affiliation University of Fukui (Univ. of Fukui)
7th Author's Name Hirohiko Kimura  
7th Author's Affiliation University of Fukui (Univ. of Fukui)
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Speaker Author-1 
Date Time 2014-01-26 14:25:00 
Presentation Time 40 minutes 
Registration for MI 
Paper # MI2013-81 
Volume (vol) vol.113 
Number (no) no.410 
Page pp.139-142 
#Pages
Date of Issue 2014-01-19 (MI) 


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