Liver segmentation from CT Image using fuzzy clustering and level set

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 cluster- ing 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 experi- ment result shows that the method can achieve high accuracy (0.9986) and specificity (0.9989). Comparing with stan- dard level set method, our method is more effective in dealing with over-segmentation problem.