Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong, SAR, People's Republic of China.
Department of Electrical and Electronic Engineering, the University of Hong Kong, Hong Kong, SAR, People's Republic of China.
Magn Reson Med. 2018 Oct;80(4):1376-1390. doi: 10.1002/mrm.27120. Epub 2018 Feb 9.
To improve simultaneous multislice (SMS) EPI by robust Nyquist ghost correction in both coil sensitivity calibration and SMS reconstruction.
To derive coil sensitivity and slice-dependent phase difference map between positive- and negative-echo images, single-band EPI reference data are fully sampled with EPI parameters matched to SMS acquisition. First, the reference data are organized into positive- and negative-echo virtual channels where missing data are estimated using low-rank-based simultaneous autocalibrating and k-space estimation (SAKE) at small matrix size. The resulting ghost-free positive- and negative-echo images are combined to generate coil sensitivity maps. Second, full-matrix positive- and negative-echo images are SENSE reconstructed from the reference data. Their phase difference or error map is then calculated. Last, SMS EPI is reconstructed using phase error correction SENSE (PEC-SENSE) that incorporates phase error map into coil sensitivity maps for negative-echo data. The proposed method was evaluated using both experimental data from 7T systems and simulations.
Virtual coil SAKE eliminated Nyquist ghosts in the single-band EPI, yielding high-quality coil sensitivity maps and phase error maps. The subsequent PEC-SENSE robustly reconstructed SMS EPI under various conditions, including presence of in-plane acceleration, with lesser artifacts and higher temporal SNR than slice-dependent 1D linear correction method.
The proposed procedure of virtual coil SAKE calibration and PEC-SENSE reconstruction substantially reduces all ghost-related artifacts originating either directly from SMS EPI data or indirectly from EPI-based coil sensitivity maps. It is computationally efficient, and generally applicable to all SMS EPI-based applications.
通过在线圈灵敏度校准和 SMS 重建中进行稳健的奈奎斯特鬼影校正,来提高同时多层(SMS)EPI。
为了导出线圈灵敏度和正、负回波图像之间的切片相关相位差图,使用与 SMS 采集匹配的 EPI 参数对单频带 EPI 参考数据进行完全采样。首先,将参考数据组织到正、负回波虚拟通道中,在小矩阵尺寸下使用基于低秩的同时自动校准和 k 空间估计(SAKE)来估计缺失数据。由此产生的无鬼影正、负回波图像被组合以生成线圈灵敏度图。其次,从参考数据中使用全矩阵正、负回波 SENSE 重建。然后计算它们的相位差或误差图。最后,使用将相位误差图合并到负回波数据的线圈灵敏度图中的相位误差校正 SENSE(PEC-SENSE)来重建 SMS EPI。该方法使用来自 7T 系统的实验数据和模拟数据进行了评估。
虚拟线圈 SAKE 消除了单频带 EPI 中的奈奎斯特鬼影,产生了高质量的线圈灵敏度图和相位误差图。随后的 PEC-SENSE 在各种条件下稳健地重建了 SMS EPI,包括平面内加速的存在,与基于切片的 1D 线性校正方法相比,具有更少的伪影和更高的时间 SNR。
虚拟线圈 SAKE 校准和 PEC-SENSE 重建的提议过程大大减少了源自 SMS EPI 数据或源自基于 EPI 的线圈灵敏度图的所有与鬼影相关的伪影。它计算效率高,并且通常适用于所有基于 SMS EPI 的应用。