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Optimal slice timing correction and its interaction with fMRI parameters and artifacts

机译：最佳切片定时校正及其与FMRI参数和伪影的交互

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摘要

Due to the nature of fMRI acquisition protocols, slices in the plane of acquisition are not acquired simultaneously or sequentially, and therefore are temporally misaligned with each other. Slice timing correction (STC) is a critical preprocessing step that corrects for this temporal misalignment. Interpolation-based STC is implemented in all major fMRI processing software packages. To date, little effort has gone towards assessing the optimal method of STC. Delineating the benefits of STC can be challenging because of its slice-dependent gain as well as its interaction with other fMRI artifacts. In this study, we propose a new optimal method (Filter-Shift) based on the fundamental properties of sampling theory in digital signal processing. We then evaluate our method by comparing it to two other methods of STC from the most popular statistical software packages, SPM and FSL. STC methods were evaluated using 338 simulated and 30 real fMRI data and demonstrate the effectiveness of STC in general as well as the superiority of the proposed method in comparison to existing ones. All methods were evaluated under various scan conditions such as motion level, interleave sequence, scanner sampling rate, and the duration of the scan itself. (C) 2016 Elsevier B.V. All rights reserved.
机译：由于FMRI采集协议的性质，不同时或顺序获取的采集平面中的切片，因此彼此逐时错位。切片定时校正（STC）是一个关键的预处理步骤，可以纠正此时间错位。基于插值的STC在所有主要的FMRI处理软件包中实现。迄今为止，很少的努力已经朝着评估STC的最佳方法。划定STC的好处可能是具有挑战性的，因为它的切片依赖性增益以及与其他FMRI伪影的相互作用。在这项研究中，我们提出了一种基于数字信号处理中采样理论的基本特性的新的最佳方法（过滤器转换）。然后，我们通过将其与来自最流行的统计软件包，SPM和FSL的STC的另外两种方法进行评估。使用338模拟和30个真实FMRI数据进行评估STC方法，并证明STC的有效性以及与现有的方法相比之下的方法的优势。在各种扫描条件下评估所有方法，例如运动水平，交错序列，扫描仪采样率和扫描本身的持续时间。 （c）2016年Elsevier B.v.保留所有权利。

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