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Liver Segmentation from CT Image Using Fuzzy Clustering and Level Set

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DOI: 10.4236/jsip.2013.43B007    3,817 Downloads   5,996 Views   Citations

ABSTRACT

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.


Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

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.

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