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Paper Abstract and Keywords
Presentation 2008-01-25 11:30
A Rule Based Technique for Liver Segmentation in CT Data
Amir H. Foruzan, Reza A. Zoroofi (Univ. of Tehran), Yoshinobu Sato, Masatoshi Hori (Osaka Univ.) MI2007-71
Abstract (in Japanese) (See Japanese page) 
(in English) Segmentation is a major step in liver image analysis and may help clinician to quantify the progression of liver diseases. A physician performs liver manual segmentation based on anatomical facts. We follow a similar approach in the proposed techniques. We first find the image slice corresponding to the largest cross-section of the liver. We regard it as the starting slice in segmentation. Using this slice, we estimate the intensity range of liver and apply the range used throughout the algorithm. We next extract bones and connect them to form a mask for liver region. By this mask, we remove some non-liver parts within the intensity range of liver. We then utilize several anatomical facts to convert gray-scale liver images to colored ones. Results reveal that the proposed technique outperforms other existing techniques in terms of speed, accuracy, sensitivity, and specificity.
Keyword (in Japanese) (See Japanese page) 
(in English) Liver boundary detection / Knowledge based segmentation / Liver segmentation / Adaptive Thresholding / Color map generation / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 461, MI2007-71, pp. 47-54, Jan. 2008.
Paper # MI2007-71 
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)
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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 English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Rule Based Technique for Liver Segmentation in CT Data 
Sub Title (in English)  
Keyword(1) Liver boundary detection  
Keyword(2) Knowledge based segmentation  
Keyword(3) Liver segmentation  
Keyword(4) Adaptive Thresholding  
Keyword(5) Color map generation  
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Keyword(7)  
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1st Author's Name Amir H. Foruzan  
1st Author's Affiliation University of Tehran, Iran. (Univ. of Tehran)
2nd Author's Name Reza A. Zoroofi  
2nd Author's Affiliation University of Tehran, Iran. (Univ. of Tehran)
3rd Author's Name Yoshinobu Sato  
3rd Author's Affiliation Osaka University Medical School (Osaka Univ.)
4th Author's Name Masatoshi Hori  
4th Author's Affiliation Osaka University Medical School (Osaka Univ.)
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Speaker Author-2 
Date Time 2008-01-25 11:30:00 
Presentation Time 10 minutes 
Registration for MI 
Paper # MI2007-71 
Volume (vol) vol.107 
Number (no) no.461 
Page pp.47-54 
#Pages 8 
Date of Issue 2008-01-18 (MI) 

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