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Paper Abstract and Keywords
Presentation 2007-09-20 15:10
Development of automated method for detection of multiple sclerosis candidate regions based on brain magnetic resonance images
Daisuke Yamamoto, Hidetaka Arimura (Kyushu Univ.), Shingo Kakeda (Univ. of Occupational and Environmental Health), Yasuo Yamashita (Kyushu Univ. Hospital), Seiji Kumazawa, Fukai Toyofuku, Yoshiharu Higashida (Kyushu Univ.), Yukunori Korogi (Univ. of Occupational and Environmental Health) MI2007-45
Abstract (in Japanese) (See Japanese page) 
(in English) The severity and symptom of multiple sclerosis (MS) depend on its location, shape, and area. It is very important to evaluate the temporal change of MS regions in terms of location, shape, and area for estimation of MS progression. Our aim of this study was to develop an automated method for detection of MS candidate regions based on three types of brain magnetic resonance (MR) images, i.e., T1-, T2-weighted images, and fluid attenuated inversion-recovery (FLAIR) images. The MS candidate regions were identified based on a multiple gray level thresholding technique and a region growing technique on a subtraction image between a T1-image and a FLAIR image. The candidate regions were determined by monitoring the interval changes of image feature values for region growing based on pixel value. Eight image features were determined for each candidate region, and many false positive regions were removed by using simple rules and a support vector machine (SVM). We applied our method to 24 slices of four MS cases, which included 80 MS regions. As a result, 87.5 % of MS regions were detected without false positives per slice.
Keyword (in Japanese) (See Japanese page) 
(in English) computer-aided diagnosis (CAD) / multiple sclerosis (MS) / magnetic resonance imaging (MRI) / image feature analysis / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 220, MI2007-45, pp. 51-52, Sept. 2007.
Paper # MI2007-45 
Date of Issue 2007-09-13 (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 2007-09-20 - 2007-09-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2007-09-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Development of automated method for detection of multiple sclerosis candidate regions based on brain magnetic resonance images 
Sub Title (in English)  
Keyword(1) computer-aided diagnosis (CAD)  
Keyword(2) multiple sclerosis (MS)  
Keyword(3) magnetic resonance imaging (MRI)  
Keyword(4) image feature analysis  
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1st Author's Name Daisuke Yamamoto  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Hidetaka Arimura  
2nd Author's Affiliation Kyushu University (Kyushu Univ.)
3rd Author's Name Shingo Kakeda  
3rd Author's Affiliation University of Occupational and Environmental Health (Univ. of Occupational and Environmental Health)
4th Author's Name Yasuo Yamashita  
4th Author's Affiliation Kyushu University Hospital (Kyushu Univ. Hospital)
5th Author's Name Seiji Kumazawa  
5th Author's Affiliation Kyushu University (Kyushu Univ.)
6th Author's Name Fukai Toyofuku  
6th Author's Affiliation Kyushu University (Kyushu Univ.)
7th Author's Name Yoshiharu Higashida  
7th Author's Affiliation Kyushu University (Kyushu Univ.)
8th Author's Name Yukunori Korogi  
8th Author's Affiliation University of Occupational and Environmental Health (Univ. of Occupational and Environmental Health)
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Speaker Author-1 
Date Time 2007-09-20 15:10:00 
Presentation Time 25 minutes 
Registration for MI 
Paper # MI2007-45 
Volume (vol) vol.107 
Number (no) no.220 
Page pp.51-52 
#Pages 2 
Date of Issue 2007-09-13 (MI) 

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