MRI denoising using Non-Local Means
MRI denoising using Non-Local Means
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DOI：
10.1016/j.media.2008.02.004
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发表时间：
2008-08-01
影响因子：
10.9
通讯作者：
Robles, Montserrat
中科院分区：
文献类型：
--
作者：
Manjon, Jose V.;Carbonell-Caballero, Jose;Robles, Montserrat
磁共振（MR）图像受随机噪声的影响，这限制了数据中任何定量测量的准确性。在目前的工作中，最近提出的随机噪声去除滤波器进行了分析和调整，以减少这种噪声在MR幅度图像。这个参数滤波器，称为非局部均值（NLM），是高度依赖于其参数的设置。本文的目的是找到最佳的参数选择MR幅度图像去噪。为此目的，已经进行了实验，以找到不同的噪声水平的最佳参数。此外，该滤波器已被适配为适合MR幅度图像中的噪声（即，Rician噪声）的特定特性。从合成和真实的图像的结果，我们可以得出结论，该滤波器可以成功地用于自动MR图像去噪。(C)2008 Elsevier B.V.保留所有权利。
Magnetic Resonance (MR) images are affected by random noise which limits the accuracy of any quantitative measurements from the data. In the present work, a recently proposed filter for random noise removal is analyzed and adapted to reduce this noise in MR magnitude images. This parametric filter, named Non-Local Means (NLM), is highly dependent on the setting of its parameters. The aim of this paper is to find the optimal parameter selection for MR magnitude image denoising. For this purpose, experiments have been conducted to find the optimum parameters for different noise levels. Besides, the filter has been adapted to fit with specific characteristics of the noise in MR magnitude images (i.e. Rician noise). From the results over synthetic and real images we can conclude that this filter can be successfully used for automatic MR image denoising. (C) 2008 Elsevier B.V. All rights reserved.