This paper presents a fully automatic segmentation method of liver CT scans using fuzzy c-mean clustering and level set. First, the contrast of original image is enhanced to make boundaries clearer; second, a spatial fuzzy c-mean clustering combining with anatomical prior knowledge is employed to extract liver region automatically; thirdly, a distance regularized level set is used for refinement; finally, morphological operations are used as post-processing. The experiment result shows that the method can achieve high accuracy (0.9986) and specificity (0.9989). Comparing with standard level set method, our method is more effective in dealing with over-segmentation problem.
In REF , spatial fuzzy -means clustering combined with anatomical prior knowledge is employed to extract liver region, while a distance regularized level set is used for refinement followed by morphological operations.
Liver Segmentation from CT Image Using Fuzzy Clustering and Level Set
Journal of Signal and Information Processing
Mathematics