  k-space undersampling is a standard technique to accelerate MR image
acquisitions. Reconstruction techniques including GeneRalized Autocalibrating
Partial Parallel Acquisition(GRAPPA) and its variants are utilized extensively
in clinical and research settings. A reconstruction model combining GRAPPA with
a conditional generative adversarial network (GAN) was developed and tested on
multi-coil human brain images from the fastMRI dataset. For various
acceleration rates, GAN and GRAPPA reconstructions were compared in terms of
peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). For an
acceleration rate of R=4, PSNR improved from 33.88 using regularized GRAPPA to
37.65 using GAN. GAN consistently outperformed GRAPPA for various acceleration
rates.
