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- Mengye Lyu, Markus Barth, Victor B Xie, Yilong Liu, Xin Ma, Yanqiu Feng, and Ed X Wu.
- Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong, SAR, People's Republic of China.
- Magn Reson Med. 2018 Oct 1; 80 (4): 1376-1390.
PurposeTo improve simultaneous multislice (SMS) EPI by robust Nyquist ghost correction in both coil sensitivity calibration and SMS reconstruction.MethodsTo 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.ResultsVirtual 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.ConclusionThe 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.© 2018 International Society for Magnetic Resonance in Medicine.
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