Makers based level set method for image segmentation

This paper presents a novel image segmentation method based on the integration of level set and marker methods. The two distinct techniques for image processing are combined in a manner to utilize the strengths of both. The internal markers obtained by extended-maxima transform bring a priori knowledge to bear on the image segmentation. The initial level set function is constructed from region of interest (ROI) on the internal markers. In this way, an automatic initialization of the level set evolution can be obtained, and the boundaries of the objects can be extracted. The cost time does not depend on the size of the image but the region of internal marker because only level set function with markers is updated instead of the level set function for each pixel. Therefore, the consumed time is greatly reduced. The efficiency and accuracy of the method are demonstrated by the experiments on the real blood vessel images and MR image.