Improved LLMMSE filter in denoising of diffusion weighted image

doi:10.3778/j.issn.1002-8331.2010.29.002

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (29): 6-8.DOI: 10.3778/j.issn.1002-8331.2010.29.002

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Improved LLMMSE filter in denoising of diffusion weighted image

YI San-li¹，CHEN Zhen-cheng²，LIN Hong-li¹

1.Biomedical Engineering Institute of Central South University，Changsha 410083，China
2.Biomedical Engineering Research Center，Guilin University of Electronic Technology，Guilin，Guangxi 541004，China

Received:2010-07-07 Revised:2010-08-23 Online:2010-10-11 Published:2010-10-11
Contact: YI San-li

改进的LLMMSE滤波器对扩散加权图像的降噪

易三莉¹，陈真诚²，林红利¹

1.中南大学信息物理工程学院生物医学工程研究所，长沙 410083
2.桂林电子科技大学生物医学工程研究中心，广西桂林 541004

通讯作者: 易三莉

Abstract

Abstract: Diffusion weighted images are characterized by multi-boundaries.Accurate boundary signals are essential in computing diffusion tensor images based on DWIs.Through the detailed analysis of the effect of the LLMMSE filter applied in denoising the image boundary，an improved LLMMSE filter based on the theory of local minimum variance is proposed.After the application of this proposed method in both simulate data and real data and the comparison of the improved method with LLMMSE，this proposed method is proved to produce better effect of denoising the boundary signals.

Key words: diffusion weighted image, LLMMSE filter, local variance

摘要： 扩散加权图像具有多边界的特点，在扩散加权图像中，准确的边界信号对扩散张量图像的计算尤其重要。通过对局部线性最小均方误差滤波器（Local Linear Minimum Mean Square Error filter，LLMMSE filter）在图像边界处降噪特点进行分析，提出基于最小方差数据集的改进的LLMMSE滤波算法。通过将所提算法应用于模拟数据及真实数据，以及与LLMMSE算法进行比较，验证了本算法具有更好的边界信号降噪能力。

关键词: 扩散加权图, LLMMSE滤波器, 局部方差

CLC Number:

R445.2

YI San-li¹，CHEN Zhen-cheng²，LIN Hong-li¹. Improved LLMMSE filter in denoising of diffusion weighted image[J]. Computer Engineering and Applications, 2010, 46(29): 6-8.

易三莉¹，陈真诚²，林红利¹. 改进的LLMMSE滤波器对扩散加权图像的降噪[J]. 计算机工程与应用, 2010, 46(29): 6-8.

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Improved LLMMSE filter in denoising of diffusion weighted image

改进的LLMMSE滤波器对扩散加权图像的降噪

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