数据采集与处理2011，Vol.26Issue(2)：194-199,6.
基于改进Random Walk算法的磁共振图像脑组织分割
MRI Brain Tissue Segmentation Based on Improved Random Walk Algorithm
摘要
Abstract
The edge weight is the most important factor in Random Walk algorithm.To improve the mapping ability of the weighting function can achieve better performance.The image local entropy is introduced into Random Walk algorithm to construct a new weighting function reflecting the changing information of adjacent-pixel' s gray value and the discrete information of local image.It improves the identification ability on homogeneous pixels and edge.The Fisher discriminate function is used to calculate the optimal classification threshold.Experimental results show that the improved algorithm performs better for identifying homogeneous content and boundary of target, and it has a better robustness to noise than the original algorithm.关键词
图像分割/Random Walk算法/局部熵/最佳阈值选取分类
信息技术与安全科学引用本文复制引用
吴德煌,刘伟,赖凯,范亚,李传富,冯焕清..基于改进Random Walk算法的磁共振图像脑组织分割[J].数据采集与处理,2011,26(2):194-199,6.基金项目
国家自然科学基金(60771007)资助项目. （60771007）
