Brain MR Image Segmentation and Bias Field Correction Using Adaptive Fuzzy C Means Model

摘要：

The imperfections in the radio-frequency coils or problems associated with the acquisition sequences may cause MRI intensity inhomogeneities, which may mislead image segmentation. Comparing the tradition fuzzy C means model, this paper adds the bias field information in the objective function for simultaneous correction of the bias field and accurately segmentation. In adaptive model, the bias field is modeled as a linear combination of a set of basis functions to ensure the smoothness and slowly varying, and can be easy estimated by computing the coefficients of this basis functions in every iteration. 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 fuzzy c means image segmentation

作者: Tianming Zhan Zhihui Wei Qi Ge Liang Xiao Jun Zhang

作者单位: School of Computer Science and Technology Nanjing University of Science and Technology Nanjing China School of Science, Nanjing University of Science and Technology Nanjing China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

会议地点: 长春

会议语种:英文

页码: 151-154

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）