Denoising 3D MR images by the enhanced non-local means filter for Rician noise
Denoising 3D MR images by the enhanced non-local means filter for Rician noise
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DOI：
10.1016/j.mri.2010.06.023
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发表时间：
2010-12-01
影响因子：
2.5
通讯作者：
Green, Richard
中科院分区：
文献类型：
--
作者：
Liu, Hong;Yang, Cihui;Green, Richard
非局部均值(NLM)滤波通过计算全局区域内像素的加权平均值来去除噪声，并显示出优于现有的仅考虑局部邻域像素的局部滤波方法。该滤波器已成功地从2D图像扩展到3D图像，并被应用于3D磁共振图像的去噪。为了提高去噪效果，本文提出了一种基于NLM滤波器的新型滤波器。考虑到MR图像中莱斯噪声的特点，首先对幅值平方的图像进行NLM滤波去噪。然后，进行无偏校正以消除有偏偏差。在进行NLM滤波时，根据高斯滤波后的图像计算权值，以减少噪声的干扰。通过将该方法与其他三种滤波器进行定性和定量的比较，即原始NLM滤波器、无偏NLM(UNLM)滤波器和RicieNLM(RNLM)滤波器，对该滤波器的性能进行了评估。实验结果表明，与其他几种滤波方法相比，该方法具有更好的去噪性能。(C)2010 Elsevier Inc.保留所有权利。
The non-local means (NLM) filter removes noise by calculating the weighted average of the pixels in the global area and shows superiority over existing local filter methods that only consider local neighbor pixels. This filter has been successfully extended from 2D images to 3D images and has been applied to denoising 3D magnetic resonance (MR) images. In this article, a novel filter based on the NLM filter is proposed to improve the denoising effect. Considering the characteristics of Rician noise in the MR images, denoising by the NLM filter is first performed on the;squared magnitude images. Then, unbiased correcting is carried out to eliminate the biased deviation. When performing the NLM filter, the weight is calculated based on the Gaussian-filtered image to reduce the disturbance of the noise. The performance of this filter is evaluated by carrying out a qualitative and quantitative comparison of this method with three other filters, namely, the original NLM filter, the unbiased NLM (UNLM) filter and the Rician NLM (RNLM) filter. Experimental results demonstrate that the proposed filter achieves better denoising performance over the other filters being compared. (C) 2010 Elsevier Inc. All rights reserved.