Hybrid-Space SENSE Reconstruction for Simultaneous Multi-Slice MRI

作者：Kangrong Zhu, Robert F. Dougherty, Hua Wu, Matthew J. Middione, Atsushi Takahashi, Tao Zhang, John M. Pauly, Adam B. Kerr · 发表于：IEEE Transactions on Medical Imaging · 年份：2016 · DOI：10.1109/tmi.2016.2531635 · 被引用次数：49 · 研究领域：Advanced MRI Techniques and Applications、Advanced Neuroimaging Techniques and Applications、NMR spectroscopy and applications

Simultaneous Multi-Slice (SMS) magnetic resonance imaging (MRI) is a rapidly evolving technique for increasing imaging speed. Controlled aliasing techniques utilize periodic undersampling patterns to help mitigate the loss in signal-to-noise ratio (SNR) in SMS MRI. To evaluate the performance of different undersampling patterns, a quantitative description of the image SNR loss is needed. Additionally, eddy current effects in echo planar imaging (EPI) lead to slice-specific Nyquist ghosting artifacts. These artifacts cannot be accurately corrected for each individual slice before or after slice-unaliasing. In this work, we propose a hybrid-space sensitivity encoding (SENSE) reconstruction framework for SMS MRI by adopting a three-dimensional representation of the SMS acquisition. Analytical SNR loss maps are derived for SMS acquisitions with arbitrary phase encoding undersampling patterns. Moreover, we propose a matrix-decoding correction method that corrects the slice-specific Nyquist ghosting artifacts in SMS EPI acquisitions. Brain images demonstrate that the proposed hybrid-space SENSE reconstruction generates images with comparable quality to commonly used split-slice-generalized autocalibrating partially parallel acquisition reconstruction. The analytical SNR loss maps agree with those calculated by a Monte Carlo based method, but require less computation time for high quality maps. The analytical maps enable a fair comparison between the performances of coherent and inc...