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Paper Abstract and Keywords
Presentation 2013-01-24 17:05
Automated segmentation of the upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ inter-relations
Shunta Hirayama, Toshiyuki Okada, Masatoshi Hori, Noriyuki Tomiyama, Yoshinobu Sato (Osaka Univ.) MI2012-91
Abstract (in Japanese) (See Japanese page) 
(in English) We have studied the automatic segmentation of multi-organ region from abdominal CT images ever. In previous work, we have proposed the automatic segmentation of multiple organ region by performing a hierarchical statistical modeling using a relationship between organs. In this paper, we have proposed automatically segmentation of the upper digestive tract from abdominal contrast-enhanced CT using segmented multi organs so far. Segment and compare the esophagus, stomach and duodenum using hierarchical statistical modeling which is our proposed method, and conventional statistical atlas method. They were evaluated quantitatively by Jaccard index and the surface distance error of the segmented region and correct region data.
Keyword (in Japanese) (See Japanese page) 
(in English) hierarchical statistical modeling / Prediction statistical atlas / gastroduodenal / esophagus / semi-supervised learning / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 411, MI2012-91, pp. 149-154, Jan. 2013.
Paper # MI2012-91 
Date of Issue 2013-01-17 (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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee MI  
Conference Date 2013-01-24 - 2013-01-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunka Tenbusu Kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Computational anatomy and its application to computer assisted diagnosis and therapy, etc 
Paper Information
Registration To MI 
Conference Code 2013-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automated segmentation of the upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ inter-relations 
Sub Title (in English)  
Keyword(1) hierarchical statistical modeling  
Keyword(2) Prediction statistical atlas  
Keyword(3) gastroduodenal  
Keyword(4) esophagus  
Keyword(5) semi-supervised learning  
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1st Author's Name Shunta Hirayama  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Toshiyuki Okada  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Masatoshi Hori  
3rd Author's Affiliation Osaka University (Osaka Univ.)
4th Author's Name Noriyuki Tomiyama  
4th Author's Affiliation Osaka University (Osaka Univ.)
5th Author's Name Yoshinobu Sato  
5th Author's Affiliation Osaka University (Osaka Univ.)
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Speaker
Date Time 2013-01-24 17:05:00 
Presentation Time 15 
Registration for MI 
Paper # IEICE-MI2012-91 
Volume (vol) IEICE-112 
Number (no) no.411 
Page pp.149-154 
#Pages IEICE-6 
Date of Issue IEICE-MI-2013-01-17 


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