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Paper Abstract and Keywords
Presentation 2014-01-27 13:30
Investigation on Classification of Benign and Malignant Masses on Mammograms by Use of Modified Local Ternary Pattern
Chisako Muramatsu, Min Zhang, Takeshi Hara (Gifu Univ), Tokiko Endo (Nagoya Medical Center), Hiroshi Fujita (Gifu Univ) MI2013-118
Abstract (in Japanese) (See Japanese page) 
(in English) We have been investigating an image analysis method for assisting the differential diagnosis of breast masses on mammograms. Our previous methods rely largely on shape and margin features based on the mass outlines. However, automatic determination of the mass contours can be difficult while the manual determination is time-consuming and subjected to inter-operator variation. In addition, the previous features related to mass density, which is one of the important findings in diagnosis, were considered not very useful. In this study, a new set of texture features was investigated for differentiation between benign and malignant masses. The local ternary pattern with reference to the radial direction was determined in regions automatically selected from the square regions of interest (ROIs) including masses. The usefulness of these features was evaluated with 58 benign ROIs and 93 malignant ROIs by a leave-one-out cross validation method using an artificial neural network. With the selected features, the classification performance was 0.82 in terms of the area under the receiver operating characteristic curve. The proposed texture features might be useful in the classification of benign and malignant masses on mammograms.
Keyword (in Japanese) (See Japanese page) 
(in English) digital mammography / breast masses / classification / computer-aided diagnosis / local ternary patterns / texture features / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 410, MI2013-118, pp. 327-330, Jan. 2014.
Paper # MI2013-118 
Date of Issue 2014-01-19 (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)
Download PDF MI2013-118

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) Investigation on Classification of Benign and Malignant Masses on Mammograms by Use of Modified Local Ternary Pattern 
Sub Title (in English)  
Keyword(1) digital mammography  
Keyword(2) breast masses  
Keyword(3) classification  
Keyword(4) computer-aided diagnosis  
Keyword(5) local ternary patterns  
Keyword(6) texture features  
Keyword(7)  
Keyword(8)  
1st Author's Name Chisako Muramatsu  
1st Author's Affiliation Gifu University (Gifu Univ)
2nd Author's Name Min Zhang  
2nd Author's Affiliation Gifu University (Gifu Univ)
3rd Author's Name Takeshi Hara  
3rd Author's Affiliation Gifu University (Gifu Univ)
4th Author's Name Tokiko Endo  
4th Author's Affiliation Nagoya Medical Center (Nagoya Medical Center)
5th Author's Name Hiroshi Fujita  
5th Author's Affiliation Gifu University (Gifu Univ)
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Speaker Author-1 
Date Time 2014-01-27 13:30:00 
Presentation Time 45 minutes 
Registration for MI 
Paper # MI2013-118 
Volume (vol) vol.113 
Number (no) no.410 
Page pp.327-330 
#Pages 4 
Date of Issue 2014-01-19 (MI) 

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