The SEM Statistical Mixture Model of Segmentation Algorithm of Brain Vessel Image

摘要：

The brain MRI images are processed with statistical analysis technology, and then 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 Gaussian Mixture Model is put forward to fit the stochastic distribution of the brain vessels and brain tissue. Finally, the SEM algorithm is adopted to estimate the parameters of Gaussian Mixture Model. The feasibility and validity of the model is verified by the experiment. With the model, small branches of the brain vessel can be segmented, the speed of the convergent is improved and local minima are avoided.

关键词： Segmentation of brain image MIP algorithm EM algorithm Mixture model Parameter estimation

作者: Xingce Wang Feng Xu Mingquan Zhou Zhongke Wu Xinyu Liu

作者单位: College of Information Science and Technology, Beijing Normal University,Beijing, China Institute of computing technology, Chinese Academy of Science,Beijing, China

会议类型: 国际会议

会议名称: International Conference on Life System Modeling and Simulation,and International Conference on Intelligent Computing for Sustainable Energy and Environment(2010生命系统建模与仿真国际会议暨m2010可持续能源与环境智能计算国际会议)

会议地点: 无锡

会议语种:英文

页码: 196-204

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）