An Anisotropic GVF Model for the MR Image Segmentation of Left Ventricle

In order to overcome the shortcomings that the traditional gradient vector flow(GVF)model is sensitive to structures with slender topology,noise and weak borders,an anisotropic GVF model based on regional information is proposed in this paper.First,the clustering information calculated by the fuzzy C-means(FCM)is applied to the GVF model in order to reduce the impact of weak borders and noise.Second,the image structure information is used to improve the GVF model,which could make the GVF model anisotropic and reduce the impact of slender topology.Finally,the anisotropic GVF model is included into the Snake equation which could guide the curves evolution to get the target border.Experiments show that the new model has better performance in segmentation.