Brain MR Image Segmentation and Bias Correction Based on Gaussian mixture model and linear regression method

摘要：

This paper presents a statistics method for segmentation and bias correction of brain MR images. The proposed model utilizes Gaussian mixture model and linear regression method to get the segmentation results and correct bias field. Experimental results on both synthetic images and MR data are given to demonstrate the effectiveness and efficiency of the proposed algorithm.

关键词： Bias field image segmentation expectation-maximization linear regression

作者: Shenghua Gu Tianming Zhan Yingchao Zhang

作者单位: Nanjing University of Information & Technology .Nanjing 210044,China School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing 210 Nanjing University of Information & Technology ,Nanjing 210044,China

会议类型: 国际会议

会议名称: 2010 International Conference on Probability and Statistics of the International Institute for General Systems Studies(国际一般系统理论研究会中国概率统计学会第二届学术会议IIGSS-CPS2010)

会议地点: 南京

会议语种:英文

页码: 719-722

在线出版日期: 2010-07-29（万方平台首次上网日期，不代表论文的发表时间）