A Novel Hybrid Kernel Function Method for Medical Images Based on Level Set
Shi Zhang, Liu Jiang, Lihong Wang, Shichang Liu · 2010
In this paper, integrating Gaussian kernel function and linear kernel function, we propose a novel hybrid segmentation method based on level set. The main contributions of this paper are to segment the medical images which are not homogeneous or uniform by using kernel function, and to give consideration to overall information and local information by using hybrid kernel function. Furthermore, our method modifies the stopping criterion; the curve of level set is close to the boundary. Experimental results for real clinical images show that the effectiveness of our method.