改进Wiener滤波弥散加权磁共振图像Rician噪声复原  

Diffusion Weighted MRI Rician Noise Restoration Using Modified Wiener Filtering

作　　者：吴锡[1,2] 何晋[1] 王玉[1] 谢明元[1] 周激流[2] 

机构地区：[1]成都信息工程大学电子工程学院,成都610225 [2]四川大学计算机学院,成都610065

出　　处：《中国生物医学工程学报》2013年第2期135-140,共6页Chinese Journal of Biomedical Engineering

基　　金：国家自然科学基金项目(81201158)

摘　　要：针对弥散加权磁共振图像噪声呈Rician分布,现有Wiener滤波基于高斯分布易于产生误差的缺陷,以及弥散加权磁共振图像多相近磁场方向数据共存特点,综合多相近磁场方向的弥散加权磁共振图像进行Wiener滤波复原,并将现有针对高斯噪声的Wiener滤波器基于Rician噪声分布进行改进,最后在估计复原参数的过程中引入各向异性概念提高复原参数估计的准确性,进一步提高复原质量。使用本方法分别在合成和真实脑部弥散加权磁共振图像上进行的仿真和实验表明,本方法能有效降低噪声对弥散加权磁共振图像的影响,提高由此计算获得弥散张量磁共振图像的大小和方向信息,在10%Rician噪声下,弥散加权磁共振图像的峰值信噪比提高10 dB,由此计算获得弥散张量磁共振图像角度平均偏移下降5度,可保障后续应用的准确性和可靠性。According to Rician noise distribution from diffusion weighted magnetic resonance image and the bias from the traditional Wiener filter which is designed for Gaussian model, this paper encapsulated multi diffusion weighted magnetic resonance images from nearby directions for Wiener filtering. In the procedure, Wiener filter was modified for Rieian noise model, and the parameters of filter were estimated through anisotropic area for further improvement of restoration. The simulation and experiment of both synthetic and in vivo diffusion weighted magnetic resonance image data demonstrated that the proposed method can effectively remove the noise in the diffusion weighted magnetic resonance image, and improve the quality and orientation information of diffusion tensor MRI. In 10% Rieian noise condition, peak signal noise ratio of diffusion weighted magnetic resonance image was increased 10 dB, and mean angular variation of diffusion tensor MRI decreased 5 degree, which ensures better accuracy and robustness of the further applications.

关 键 词：弥散加权磁共振图像 去噪 改进Wiener滤波 Rician噪声 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]