Self-Calibrated GRAPPA Operator Gridding (SC-GROG) for radially encoded Multi-Slice (SMS) Imaging

This work proposes a novel approach using Self-calibrating GRAPPA operator gridding (SC-GROG) for radially encoded simultaneous multi-slice imaging (SMS). The proposed method is implemented by combining non-Cartesian (NC) under-sampling (radial) with CAIPRINHA phase manipulation to accelerate data acquisition in SMS. Radial datasets are gridded using SC-GROG and reconstructed iteratively using Projection onto convex sets (POCS) algorithm. The results are compared with conventional NUFFT with POCS at increasing accelerations factors and quantified in terms of SSIM, PSNR and Artifact Power. It can be inferred from the results that the proposed method produces accurate reconstructions of SMS datasets.