Level Set Image Segmentation Method Based on Prior Shape Knowledge
基于先验形状信息的水平集图像分割

A shape-prior based on image segmentation method was proposed to approach the defect of the current level set method in segmenting the subject with strong noise and weak boundary. By using level set method,this model combines region and boundary information together and selects the optimal prior shape by Similarity Matching. The model displays its advantages in the segmentation of complicated image with strong noise and weak boundary,and in the efficicncy to solve the problems of confirming the primary contour of curve evolution. Compared with traditional way, the experiment proves that this approach contributes better segmenting effect and improved accuracy.