A level set based deformable model for segmentation of human brain MR images

Abstract

Segmentation of brain tissue from non-brain tissue, also known as skull stripping, has been challenging due to the complexity of anatomical brain structures and variable parameters of MR imaging modalities. It has been one of the most important preprocessing steps in medical image analysis. We propose a new brain segmentation algorithm that is based on a level set based deformable model. Two different sources of forces are proposed to evolve the level set-based contour. First, the brain surface attraction force is calculated based on the gray level intensity distribution of the brain, which is designed to automatically adjust the intensive parameters in response to different slices. The other force is a morphological smoothing force based on the mean curvature, which is further weighted by the differences between the mean intensity values inside and outside the contour to the zero level set intensity values. Experimental results indicated that the proposed algorithm is effectively accurate and robust, which is a promising tool in many skull stripping applications.