The Gaussian Mixture Model Clustering of Medical Image Based on Initialization of Approximate Density Function

The performance of EM algorithm heavily depends on the initial values of the parameters in EM.In this paper, The approximate density function is adopted to initialize EM.The method estimate samples by the approximate density function and statistics mixturerate,mean value,and covariance.The application of these parameters in analysis of Gaussian Mixture Desity Mode based on real human abdomen medical images and the results of experiments show that it can achieve better effect than Kmeans and random initialization.