Griswold Mark A, Jakob Peter M, Heidemann Robin M, Nittka Mathias, Jellus Vladimir, Wang Jianmin, Kiefer Berthold, Haase Axel
Julius-Maximilians Universität Würzburg, Physikalisches Institut, Würzburg, Germany.
Magn Reson Med. 2002 Jun;47(6):1202-10. doi: 10.1002/mrm.10171.
In this study, a novel partially parallel acquisition (PPA) method is presented which can be used to accelerate image acquisition using an RF coil array for spatial encoding. This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD-AUTO-SMASH reconstruction techniques. As in those previous methods, a detailed, highly accurate RF field map is not needed prior to reconstruction in GRAPPA. This information is obtained from several k-space lines which are acquired in addition to the normal image acquisition. As in PILS, the GRAPPA reconstruction algorithm provides unaliased images from each component coil prior to image combination. This results in even higher SNR and better image quality since the steps of image reconstruction and image combination are performed in separate steps. After introducing the GRAPPA technique, primary focus is given to issues related to the practical implementation of GRAPPA, including the reconstruction algorithm as well as analysis of SNR in the resulting images. Finally, in vivo GRAPPA images are shown which demonstrate the utility of the technique.
在本研究中,提出了一种新型部分并行采集(PPA)方法,该方法可用于利用射频线圈阵列进行空间编码来加速图像采集。这种技术,即广义自校准部分并行采集(GRAPPA),是PILS和VD - AUTO - SMASH重建技术的扩展。与那些先前的方法一样,在GRAPPA重建之前不需要详细、高精度的射频场图。该信息从除正常图像采集之外获取的几条k空间线中获得。与PILS一样,GRAPPA重建算法在图像组合之前从每个组件线圈提供无混叠图像。由于图像重建和图像组合步骤是在单独的步骤中执行的,这导致了更高的信噪比和更好的图像质量。在介绍GRAPPA技术之后,主要关注与GRAPPA实际应用相关的问题,包括重建算法以及所得图像中信噪比的分析。最后,展示了体内GRAPPA图像,证明了该技术的实用性。