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Paper Abstract and Keywords
Presentation 2007-01-27 11:25
Automated Determination of the Liver Boundary in CT Data Based on Anatomical knowledge and Level Set Method
Amir .H. Foruzan, Reza A. Zoroofi (Univ. of Tehran), Yoshinobu Sato, Masatoshi Hori, Takamichi Murakami, Hironobu Nakamura, Shinichi Tamurab (Osaka Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Quantitative analysis of the liver CT images is clinically important in corresponding diagnosis, treatment and surgical planning procedures. Automatic determination of the liver boundary in CT images is difficult due to similar intensity of liver with respect to its surrounding tissues, poor in-plane and inter-plane resolutions, and partial volume effect. Due to considerable changes in the location and size of the liver tissues in the abdominal duct, making robust anatomical and intensity based assumptions as well as developing robust segmentation procedures are necessary for liver boundary determination. In this research, we automatically extract required parameters according to specific features of the liver tissues. We then employ an active contour method to estimate the final boundary of the liver. After careful investigation of several donor data sets, acquired for liver transplantation, we propose a multi-step approach based on anatomical knowledge about the liver as follows. (1) We estimate the largest liver mask in the abdomen by conventional thresholding and morphological operations. (2) The mask is utilized for accurate estimation of the liver intensity range with respect to other surrounding tissues. (3) We then convert the liver gray images to color images by a heuristic color map transformation. (4) A texture analysis technique based on rotational invariant property and wavelet transform are employed to extract important features of liver regions. Based on this, liver initial boundary is estimated. (5) We employ the boundaries corresponding to initial liver regions in a level set based active contours and refine it to the final liver mask. Experiments in the presence of 4000 CT images (acquired from 20 donors) confirm the success of the proposed techniques.
Keyword (in Japanese) (See Japanese page) 
(in English) Liver Segmentation / Texture Based Segmentation / Wavelet / Active contours / Level Set / / /  
Reference Info. IEICE Tech. Rep., vol. 106, no. 510, MI2006-179, pp. 83-86, Jan. 2007.
Paper # MI2006-179 
Date of Issue 2007-01-20 (MI) 
ISSN Print edition: ISSN 0913-5685
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Conference Information
Committee MI  
Conference Date 2007-01-26 - 2007-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) the Cheju National Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2007-01-MI 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automated Determination of the Liver Boundary in CT Data Based on Anatomical knowledge and Level Set Method 
Sub Title (in English)  
Keyword(1) Liver Segmentation  
Keyword(2) Texture Based Segmentation  
Keyword(3) Wavelet  
Keyword(4) Active contours  
Keyword(5) Level Set  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Amir .H. Foruzan  
1st Author's Affiliation University of Tehran (Univ. of Tehran)
2nd Author's Name Reza A. Zoroofi  
2nd Author's Affiliation University of Tehran (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.)
5th Author's Name Takamichi Murakami  
5th Author's Affiliation Osaka University Medical School (Osaka Univ.)
6th Author's Name Hironobu Nakamura  
6th Author's Affiliation Osaka University Medical School (Osaka Univ.)
7th Author's Name Shinichi Tamurab  
7th Author's Affiliation Osaka University Medical School (Osaka Univ.)
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Speaker Author-2 
Date Time 2007-01-27 11:25:00 
Presentation Time 15 minutes 
Registration for MI 
Paper # MI2006-179 
Volume (vol) vol.106 
Number (no) no.510 
Page pp.83-86 
#Pages
Date of Issue 2007-01-20 (MI) 


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