A New robust Level Set image segmentation method based Signed Pressure Force function : Application to Medical Images

Abstract

Segmentation is an extremely active field of research since it is an important step in the treatment and the interpretation of the medical images. It represents one of the most difficult step for relevant parameters extraction from images. In this paper, we study A New robust Level Set image segmentation method is developed by formulating Signed Pressure Force Function (SPF). The advantages of this method are Firstly, the Function of Signed Pressure can efficiently stop the contours at weak or blurred edges, Second, exterior and interior boundaries can be detected no matter where the initial contour starts. We compare this method with Chan Vese (C-V) model and Geodesic Active Contours (GAC). The performance of each method can be evaluated either visually, or from similarity measurements between a reference and the results of the segmentation. We have applied each method for different medical images. Through simulated results, we have demonstrated that the best results are achieved by the proposed method.