Segmentation of Brain MR Images Based on t-mizture Model

摘要：

As Magnetic Resonance Imaging (MRI) is an important technology of radiological evaluation and computeraided diagnosis, the accuracy of the MR image segmentation directly influences the validity of following processing. The paper concerns medical image segmentation based on t-mixture model because of merits of the model. By analyzing the features of MR images, the main procedure of white matter segmentation of brain MR Images based on t-mixture model is outlined follows. The parameters of t-mixture model for the image are firstly estimated. Then the posterior probabilities of the pixels of the image are computed. At last, the image is segmented according to the Bayes decision rule for minimum error. Experimental results show that t-mixture model fits for medical image segmentation.

关键词： t-mizture model ezpectation-mazimization(EM) MRI segmentation white matter

作者: Haifeng Zhao Xingming Xu Sibao Chen Bin Luo

作者单位: Key Lab of Intelligent Computing & Signal Processing of Ministry of Education,School of Computer Science and Technology,Anhui University,Hefei,230039,P.R.China

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-4

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）