Noise estimation in single- and multiple-coil magnetic resonance data based on statistical models
Noise estimation in single- and multiple-coil magnetic resonance data based on statistical models
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DOI：
10.1016/j.mri.2009.05.025
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发表时间：
2009-12-01
影响因子：
2.5
通讯作者：
Alberola-Lopez, Carlos
中科院分区：
文献类型：
--
作者：
Aja-Fernandez, Santiago;Tristan-Vega, Antonio;Alberola-Lopez, Carlos
噪声估计是磁共振成像 (MRI) 中的一项具有挑战性的任务，可应用于质量评估、滤波或扩散张量估计。本文对基于莱斯模型的主要噪声估计器进行了重新审视和分类，并提出了新的有用方法。此外，所有调查的估计器都扩展到非中心 chi 模型，该模型适用于多线圈 MRI 和一些用于加速采集的重要并行成像算法。所提出的新的噪声估计程序基于局部矩的分布，在广泛的实验中在较小的方差和无偏估计方面表现出更好的性能，并且具有不需要显式分割图像背景的额外优点。 (C) 2009 Elsevier Inc. 保留所有权利。
Noise estimation is a challenging task in magnetic resonance imaging (MRI), with applications in quality assessment, filtering or diffusion tensor estimation. Main noise estimators based oil the Rician model are revisited and classified in this article, and new useful methods are proposed. Additionally, all the surveyed estimators are extended to the noncentral chi model, which applies to multiple-coil MRI and some important parallel imaging algorithms for accelerated acquisitions. The proposed new, noise estimation procedures, based oil the distribution of local moments, show better performance in terms of smaller variance and unbiased estimation over a wide range of experiments, with the additional advantage of not needing to explicitly segment the background of the image. (C) 2009 Elsevier Inc. All rights reserved.