Segmentation Algorithm of Brain Vessel Image Based on SEM Statistical Mixture Model

Due to the complicated structure and small proportion of brain vessels,a statistical analysis technology is proposed for its segmentation,and the accuracy of segmentation is improved by the random assortment iteration.First the MIP algorithm is applied to decrease the quantity of mixing elements.Then the Gauss Mixture Model is put forward to fit the stochastic distribution of the brain vessels and brain tissue.At last,the Stochastic Estimation Maximization(SEM)algorithm is adopted to estimate the parameters of Gauss Mixture Model.With the model,the small branches of the brain vessel can be segmented,the speed of the convergent is improved and local minima are avoided.The feasibility and validity of the model are verified by the experiment.