Vessel segmentation under non-uniform illumination: a level set approach

Abstract

In this paper, a new level set segmentation model is proposed and is coupled with the geometric information, the edge information and the region information. The new level set segmentation model is aimed at a vessel segmentation in a non-uniform image with weak object boundaries. First, a multiscaled filter with a Hessian matrix, which has a anisotropic character, is used to identify the direction of vessels. Second, the edge information is embed into a energy functional by a fast edge integral method with a laplacian zero crossing algorithm. A new level set segmentation model based on information of geometric structure, edge and region is constructed by this method. This new model can segment vessels exactly on grayscale uneven images. Compared to GAC CV segmentation model and other improved models based on CV model, the method in this paper has a better accuracy and robustness. © 2012 ISCAS.