This paper presents an approach for kidney segmentation on abdominal CT images as the first step of a virtual reality
surgery system. Segmentation for medical images is often challenging because of the objects' complicated anatomical
structures, various gray levels, and unclear edges. A coarse to fine approach has been applied in the kidney segmentation
using Chan-Vese model (C-V model) and anatomy prior knowledge. In
pre-processing stage, the candidate kidney
regions are located. Then C-V model formulated by level set method is applied in these smaller ROI, which can reduce
the calculation complexity to a certain extent. At last, after some mathematical morphology procedures, the specified
kidney structures have been extracted interactively with prior knowledge. The satisfying results on abdominal CT series
show that the proposed approach keeps all the advantages of C-V model and overcome its disadvantages.
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