Ritter Petra, Becker Robert, Graefe Christine, Villringer Arno
Berlin NeuroImaging Center and Charité, Universitätsmedizin Berlin, Berlin, Germany.
Magn Reson Imaging. 2007 Jul;25(6):923-32. doi: 10.1016/j.mri.2007.03.005. Epub 2007 Apr 26.
Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has become a widely used application in spite of EEG perturbations due to electromagnetic interference in the MR environment. The most prominent and disturbing artifacts in the EEG are caused by the alternating magnetic fields (gradients) of the MR scanner. Different methods for gradient artifact correction have been developed. Here we propose an approach for the systematic evaluation and comparison of these gradient artifact correction methods. Exemplarily, we evaluate different algorithms all based on artifact template subtraction--the currently most established means of gradient artifact removal. We introduce indices for the degree of gradient artifact reduction and physiological signal preservation. The combination of both indices was used as a measure for the overall performance of gradient artifact removal and was shown to be useful in identifying problems during artifact removal. We demonstrate that the evaluation as proposed here allows to reveal frequency-band specific performance differences among the algorithms. This emphasizes the importance of carefully selecting the artifact correction method appropriate for the respective case.
尽管在磁共振（MR）环境中，脑电图（EEG）会受到电磁干扰的影响，但同时进行脑电图（EEG）和功能磁共振成像（fMRI）已成为一种广泛应用的技术。脑电图中最突出且令人困扰的伪影是由MR扫描仪的交变磁场（梯度）引起的。人们已经开发出了不同的梯度伪影校正方法。在此，我们提出一种对这些梯度伪影校正方法进行系统评估和比较的方法。作为示例，我们评估了所有基于伪影模板减法的不同算法——这是目前最常用的梯度伪影去除方法。我们引入了梯度伪影减少程度和生理信号保留的指标。这两个指标的组合被用作梯度伪影去除整体性能的度量，并被证明在识别伪影去除过程中的问题时很有用。我们证明，此处提出的评估方法能够揭示算法之间特定频带的性能差异。这强调了针对具体情况仔细选择合适的伪影校正方法的重要性。
