A Method to Assess Spatially Variant Noise in Dynamic MR Image Series
A Method to Assess Spatially Variant Noise in Dynamic MR Image Series
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DOI：
10.1002/mrm.22258
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发表时间：
2010-03-01
影响因子：
3.3
通讯作者：
Simonetti, Orlando P.
中科院分区：
文献类型：
--
作者：
Ding, Yu;Chung, Yiu-Cho;Simonetti, Orlando P.
利用并行成像技术精确测量MR图像中的空间变化噪声是一项挑战。基于图像的噪声测量方法，如美国国家电气制造商协会提出的减法或多重采集法，由于运动和/或动态对比度的变化，往往不能在体内应用。基于Karhunen-Loeve变换和随机矩阵理论，提出了一种准确评估具有时间冗余的图像序列噪声方差的新方法。该方法将图像序列的时间协方差矩阵特征值的概率密度函数拟合到Marcenko-Pastur分布。通过数值模拟和MR噪声测量实验验证了该方法的准确性。通过与多次获取方法的对比，验证了该方法导出静态幻影的g因子图的能力。将该方法应用于体内心脏和大脑图像序列，结果分别与减法和多重采集方法一致。这种新的基于图像的噪声测量方法为从多帧图像序列中回顾性评估噪声水平和/或g因子图提供了一种实用的方法。中华医学杂志(3):782-789,2010。(C) 2010 Wiley-Liss, Inc。
Accurate measurement of spatially variant noise in MR images acquired using parallel imaging techniques is challenging. Image-based noise measurement methods such as the subtraction method proposed by the National Electrical Manufacturers Association or the multiple acquisition method often cannot be applied in vivo due to motion and/or dynamic contrast changes. Based on the Karhunen-Loeve transform and random matrix theory, we propose a novel method to accurately assess the noise variance in image series bearing temporal redundancy. The method fits the probability density function of eigenvalues from the temporal covariance matrix of the image series to the Marcenko-Pastur distribution. The accuracy of our method was validated using numerical simulation and an MR noise measurement experiment. The ability of this method to derive the g-factor map of a static phantom was validated against the multiple acquisition method. The method was applied to in vivo cardiac and brain image series and the results agreed with subtraction and multiple acquisition methods, respectively. This new image-based noise measurement method provides a practical means of retrospectively evaluating the noise level and/or g-factor map from multiframe image series. Magn Reson Med 63:782-789, 2010. (C) 2010 Wiley-Liss, Inc.