Liver parenchyma segmentation by FCM-based confidence connected region growing method

A FCM-based segmentation algorithm is proposed in this paper to improve the accuracy and efficiency of liver parenchyma segmentation. The proposed segmentation method consists of four steps as follows:First,we characterized the gray distribution of the unfiltered image. Second, combined with the Otsu algorithm and associated with a cropped liver image, we defined a gray interval as the liver's intersity range. Third, The fuzzy c-means clustering algorithm was applied to define the confidence interval of traditional confidence connectivity method. Finally, we employed the improved confidence connected algorithm to extract the liver parenchyma from a large cross-section liver image. Experimental results show that the proposed segmentation method is feasible even for diseased liver images.