Paper Info
Title
Automatic Multi-Scale Segmentation Of Intrahepatic Vessel In Ct Images For Liver Surgery Planning
Abstract
The processing of blood vessels is an indispensable part in complicated surgeries of livers and hearts as the development of medical image technologies, which requires an automatic segmentation system over CT images of organs. However, the vascular pattern of livers in CT images suffers from low contrast to background so that the existing segmentation technologies are not able to extract the blood vessels completely. In the paper, we propose a new algorithm to extract the blood vessels of livers based on the adaptive multi-scale segmentation. First, we prove that the background histogram of normal scale blood vessels obeys the Gaussian distribution in CT images, and obtain the vascular distribution function from the vascular signal segmented from the background with a local optimal threshold. Second, Hessian matrix is employed to enhance the thin blood vessels before the extraction, and a complete and clear segmentation system for blood vessels is constructed by combining the major and thin blood vessels via filtering. Experimental results show the effectiveness of the proposed method, which is able to extract more complete blood vessels for 3D system, and assist the clinical liver surgeries efficiently.
Year
DOI
Venue
2013
10.1142/S0218001413570012
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
DocType
Volume
Gray Histogram, liver vessels segmentation, Gaussian distribution, Hessian matrix
Journal
27
Issue
ISSN
Citations 
1
0218-0014
2
PageRank 
References 
Authors
0.38
11
6
Name
Order
Citations
PageRank
Yi Wang130.74
Bin Fang278453.47
Jingrui Pi320.71
Lei Wu420.38
patrick s p wang530347.66
Hongguang Wang67024.23