Multi-scale Level Set Method for Medical Image Segmentation without Re-initialization

This paper presents a novel level set method to segment medical image with intensity inhomogeneity (IIH). The multi-scale segmentation idea is incorporated and a new penalty energy term is proposed to eliminate the time-consuming re-initialization procedure. Firstly, the circular window is used to define the local region so as to approximate the image as well as IIH. Then, multi-scale statistical analysis is performed on intensities of local circular regions center in each pixel. The multi-scale energy term can be constructed by fitting multi-scale approximation of inhomogeneity-free image in a piecewise constant way. In addition, a new penalty energy term is constructed to enforce level set function to maintain a signed distance function near the zero level set. Finally, the multi-scale segmentation is performed by minimizing the total energy functional. The experiments on medical images with IIH have demonstrated the efficiency and robustness of the proposed method.