Modified fast marching and level set method for medical image segmentation

In this paper, an interactive segmentation method that combines fast marching and level set method is proposed. Level set segmentation involves solving the energy-based active contour minimization problems by the computation of geodesies or minimal distance curves. First, by selecting the seed point, the fast marching method is used to extract rough boundaries of the interested object. We modified the traditional fast marching method to capture the weak edges by introducing watershed transform. Then, the contour obtained from the fast marching method mentioned above is regarded as an initialization and the level set method is used to finely tune the contour. The algorithm is demonstrated on some medical images: segmentation of knee tissues in CT image and segmentation of brain tissues in MR image. The results show that this method can remove the small regions obtained from fast marching method and converge the desired boundary.