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首页> 外文期刊>Magnetic resonance imaging: An International journal of basic research and clinical applications >An empirical study of the maximum degree of undersampling in compressed sensing for T-2*-weighted MRI
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An empirical study of the maximum degree of undersampling in compressed sensing for T-2*-weighted MRI

机译：T-2 *重-Wii的压缩检测中欠采样的最大程度的实证研究

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摘要

Magnetic Resonance Imaging (MRI) is one of the most dynamic and safe imaging modalities used in clinical routine today. Yet, one major limitation to this technique resides in its long acquisition times. Over the last decade, Compressed Sensing (CS) has been increasingly used to address this issue and offers to shorten MR scans by reconstructing images from undersampled Fourier data. Nevertheless, a quantitative guide on the degree of acceleration applicable to a given acquisition scenario is still lacking today, leading in practice to a trial-and-error approach in the selection of the appropriate undersampling factor. In this study, we shortly point out the existing theoretical sampling results in CS and their limitations which motivate the focus of this work: an empirical and quantitative analysis of the maximum degree of undersampling allowed by CS in the specific context of T-2*-weighted MRI. We make use of a generic method based on retrospective undersampling to quantitatively deduce the maximum acceleration factor R-max which preserves a desired image quality as a function of the image resolution and the available signal-to-noise ratio (SNR). Our results quantify how larger acceleration factors can be applied to higher resolution images as long as a minimum SNR is guaranteed. In practice however, the maximum acceleration factor for a given resolution appears to be constrained by the available SNR inherent to the considered acquisition. Our analysis enables to take this a priori knowledge into account, allowing to derive a sequence-specific maximum acceleration factor adapted to the intrinsic SNR of any MR pipeline. These results obtained on an analytical T-2*-weighted phantom image were corroborated by prospective experiments performed on MR data collected with radial trajectories on a 7 T scanner with the same contrast. The proposed framework allows to study other sequence weightings and therefore better optimize sequences when accelerated using CS.
机译：磁共振成像（MRI）是今天临床常规中使用的最动力和安全的成像模式之一。然而，对该技术的一个主要限制驻留在其长时间的时间。在过去的十年中，压缩传感（CS）越来越多地用于解决这个问题，并通过从under采样的傅立叶数据重​​建图像来缩短MR扫描。尽管如此，目前仍然缺乏适用于给定的收购情景的加速度的定量指南，在练习中，在选择适当的欠采样因子时，在实践中导致效果。在这项研究中，我们很快指出了CS的现有理论采样结果及其局限性，激励了这项工作的重点：对CS在T-2 *的特定上下文中允许的欠采样程度的实证和定量分析 - 加权MRI。我们利用基于回顾性缺点的通用方法来定量地推断最大加速度因子R-MAX，其保留所需的图像质量作为图像分辨率的函数和可用的信噪比（SNR）。我们的结果量化了只要保证最小SNR，就可以将更大的加速度因子应用于更高分辨率图像。然而，在实践中，给定分辨率的最大加速度因子似乎受到考虑采集所固有的可用SNR的约束。我们的分析使得能够考虑到这一先验知识，允许从任何MR管道的内在SNR获得序列特定的最大加速因子。通过对在7 T扫描仪上的7 T扫描仪上采用径向轨迹的MR数据进行的前瞻性实验来证实，在分析T-2 * - 重量幽灵图像上获得的这些结果得到证实。所提出的框架允许研究其他序列权重，因此在使用CS加速时更好地优化序列。

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