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 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.

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X. Li, S. Luo and J. Li, "Liver Segmentation from CT Image Using Fuzzy Clustering and Level Set," Journal of Signal and Information Processing, Vol. 4 No. 3B, 2013, pp. 36-42. doi: 10.4236/jsip.2013.43B007.

Conflicts of Interest

The authors declare no conflicts of interest.


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