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Paper Abstract and Keywords
Presentation 2008-01-25 13:00
Liver Segmentation in 3D Abdominal CT Images Based on Maximum a Posterior Probability Method and Ensemble Learning
Shinya Tanaka, Akinobu Shimizu, Daisuke Furukawa, Hidefumi Kobatake (TUAT), Shigeru Nawano (Center for Radiological Sciences, IUHW), Kenji Shinozaki (NKCC) MI2007-88
Abstract (in Japanese) (See Japanese page) 
(in English) This paper describes improvements of the liver region segmentation algorithm using three phase abdominal 3D CT images , namely, early, portal and late phase images. First, the segmentation algorithm performs registration of the three phase images using Radial Basis Function. Second it extracts normal liver region as well as abnormal regions such as cancer and necrosis. Finally the extracted regions are integrated into one to define a liver region. This paper proposes a maximum a posteriori based method that extracts not only normal liver regions but also surrounding organs so as to reduce the false positives caused by the surrounding organs. A novel cancer segmentation algorithm trained by an AdaBoost algorithm is also proposed to deal with wide variety of cancers. We present the experimental results of applying the proposed method to actual 3D images and discussion about its effectiveness.
Keyword (in Japanese) (See Japanese page) 
(in English) Abdominal CT Images / Liver region segmentation / Radial Basis Function / Probabilistic Atlas / EM-algorothm / Maximum a Posteriori / AdaBoost /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 461, MI2007-88, pp. 123-130, Jan. 2008.
Paper # MI2007-88 
Date of Issue 2008-01-18 (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 MI2007-88

Conference Information
Committee MI  
Conference Date 2008-01-25 - 2008-01-26 
Place (in Japanese) (See Japanese page) 
Place (in English) Naha-Bunka-Tenbusu 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging 
Paper Information
Registration To MI 
Conference Code 2008-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Liver Segmentation in 3D Abdominal CT Images Based on Maximum a Posterior Probability Method and Ensemble Learning 
Sub Title (in English)  
Keyword(1) Abdominal CT Images  
Keyword(2) Liver region segmentation  
Keyword(3) Radial Basis Function  
Keyword(4) Probabilistic Atlas  
Keyword(5) EM-algorothm  
Keyword(6) Maximum a Posteriori  
Keyword(7) AdaBoost  
Keyword(8)  
1st Author's Name Shinya Tanaka  
1st Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
2nd Author's Name Akinobu Shimizu  
2nd Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
3rd Author's Name Daisuke Furukawa  
3rd Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
4th Author's Name Hidefumi Kobatake  
4th Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
5th Author's Name Shigeru Nawano  
5th Author's Affiliation Center for Radiological Sciences, International University of Health and Welfare (Center for Radiological Sciences, IUHW)
6th Author's Name Kenji Shinozaki  
6th Author's Affiliation National Kyusyu Cancere Center (NKCC)
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Speaker Author-1 
Date Time 2008-01-25 13:00:00 
Presentation Time 60 minutes 
Registration for MI 
Paper # MI2007-88 
Volume (vol) vol.107 
Number (no) no.461 
Page pp.123-130 
#Pages 8 
Date of Issue 2008-01-18 (MI) 

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