Abstract:  In Computed Tomography (CT) scans of liver it exists many noises. Besides, liver tumor’s gray level is very close to the liver and the tumor has fuzzy boundaries, it is hard to be segmented. During liver tumor segmentation, the traditional level set method is sensitive to initial contours and needs to adjust the parameters manually, and the time complexity is high. According to liver tumor’s fuzziness, this paper proposed a new segmentation method for liver tumor based on three dimension region of interest (3D ROI) and spatial fuzzy c-means clustering (FCMS). First it picks the ROI in three dimensions, then uses FCMS to segment the tumor, then does morphology operation, in the end uses variational B-spline level sets method to smooth the contour. The result of test turns out that, the method proposed in this paper gets better result and higher efficiency, which is also easy to operate.

Key words: liver tumor segmentation, 3D ROI, FCMS, morphology, level set