A Fast Method to Segment the Liver According to Couinaud's Classification

Authors:
Shao-Hui Huang;Bo-Liang Wang;Ming Cheng;Wei-Li Wu;Xiao-Yang Huang;Ying Ju
Affiliations:
Computer Science Department, Xiamen University, Xiamen, China 361005;Computer Science Department, Xiamen University, Xiamen, China 361005;Computer Science Department, Xiamen University, Xiamen, China 361005;Computer Science Department, Xiamen University, Xiamen, China 361005;Computer Science Department, Xiamen University, Xiamen, China 361005;Computer Science Department, Xiamen University, Xiamen, China 361005
Venue:
Medical Imaging and Informatics
Year:
2008

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Abstract

For establishing a plan of Living Donor Liver Transplantation (LDLT), it is very important to estimate the volume of each liver segment. Usually Couinaud's classification is used to segment a liver, which is based on the liver anatomy. However, it is not easy to perform this method in a 3D space directly. In this paper, a fast segment method based on the hepatic vessel tree was proposed. This method was composed of four main steps: vasculature segmentation, 3D thinning, vascular tree pruning and classification, and vascular projection and curve fitting. This method was validated by application to a 3D liver from CT data, and it was shown to approximate closely Couinaud's classification with high speed.