In order to solve the difficulties of complex background, fuzzy boundary, and uneven local part in the segmentation of medical images, an united active contours model based on relative fuzzy connectedness was proposed. First, the curve evolution equation of the active contours model and the related theories of the fuzzy connectedness were introduced in detail. Then, the relative fuzzy connectedness was introduced into the curve evolution equation as the driving force. Finally, comparative experiments showed the efficacies of the proposed method for multi-object medical images and complex medical images. Because the fuzzy connectedness combined the local information and global information, the proposed method overcome the problems of Li method for falling into local optimum boundary and Chan-Vese method unable to cross the local pseudo-boundary, and then the curve of the united active contours converged to the global optimum boundary.
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