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首页> 外文期刊>Magnetic resonance imaging: An International journal of basic research and clinical applications >Influence of multichannel combination, parallel imaging and other reconstruction techniques on MRI noise characteristics
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Influence of multichannel combination, parallel imaging and other reconstruction techniques on MRI noise characteristics

机译:多通道组合,并行成像和其他重建技术对MRI噪声特征的影响

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The statistical properties of background noise such as its standard deviation and mean value are frequently used to estimate the original noise level of the acquired data. This requires the knowledge of the statistical intensity distribution of the background signal, that is, the probability density of the occurrence of a certain signal intensity. The influence of many new MRI techniques and, in particular, of various parallel-imaging methods on the noise statistics has neither been rigorously investigated nor experimentally demonstrated yet. In this study, the statistical distribution of background noise was analyzed for MR acquisitions with a single-channel and a 32-channel coil, with sum-of-squares (SoS) and spatial-matched-filter (SMF) data combination, with and without parallel imaging using k-space and image-domain algorithms, with real-part and conventional magnitude reconstruction and with several reconstruction filters. Depending on the imaging technique, the background noise could be described by a Rayleigh distribution, a noncentral chi-distribution or the positive half of a Gaussian distribution. In particular, the noise characteristics of SoS-reconstructed multichannel acquisitions (with k-space-based parallel imaging or without parallel imaging) differ substantially from those with image-domain parallel imaging or SMF combination. These effects must be taken into account if mean values or standard deviations of background noise are employed for data analysis such as determination of local noise levels. Assuming a Rayleigh distribution as in conventional MR images or a noncentral chi-distribution for all multichannel acquisitions is invalid in general and may lead to erroneous estimates of the signal-to-noise ratio or the contrast-to-noise ratio. (C) 2008 Elsevier Inc. All rights reserved.
机译:背景噪声的统计特性(例如其标准偏差和平均值)经常用于估计所采集数据的原始噪声水平。这需要了解背景信号的统计强度分布,即一定信号强度出现的概率密度。许多新的MRI技术(尤其是各种平行成像方法)对噪声统计的影响尚未经过严格的研究或实验证明。在这项研究中,分析了单通道和32通道线圈,平方和(SoS)和空间匹配滤波器(SMF)数据组合的MR采集的背景噪声的统计分布。无需使用k空间和图像域算法进行并行成像,即可进行实部和常规幅度重建,并具有多个重建滤波器。根据成像技术的不同,背景噪声可以用瑞利分布,非中心Chi分布或高斯分布的正一半来描述。特别是,SoS重构的多通道采集(具有基于k空间的并行成像或不具有并行成像)的噪声特性与具有像域并行成像或SMF组合的噪声特性大不相同。如果将背景噪声的平均值或标准偏差用于数据分析(例如确定局部噪声水平),则必须考虑这些影响。对于所有多通道采集,假定像常规MR图像中那样的瑞利分布或非中心chi分布通常是无效的,并且可能导致信噪比或对比度与噪声比的错误估计。 (C)2008 Elsevier Inc.保留所有权利。

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