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S. Luo, Q. Hu, X. He, J. Li, J. Jin and M. Park, “Automatic Liver Parenchyma Segmentation from Abdominal CT Images Using Support Vector Machines,” Proceedings of 2009 Icme International Conference on Complex Medical Engineering, Tempe, 9-11 April 2009, pp. 1-5.

has been cited by the following article:

• TITLE: Liver Segmentation from CT Image Using Fuzzy Clustering and Level Set

  AUTHORS: Xuechen Li, Suhuai Luo, Jiaming Li

  KEYWORDS: Liver Segmentation; Fuzzy c-Mean Clustering; Level Set

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.4 No.3B, October 16, 2013

  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.