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arXiv · 2101.03135

GRAPPA-GANs for Parallel MRI Reconstruction

Nader Tavaf·Amirsina Torfi·Kamil Ugurbil·Pierre-Francois Van de Moortele
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Abstract

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.

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Nader Tavaf, Amirsina Torfi, Kamil Ugurbil, Pierre-Francois Van de Moortele. 2021-01-05. GRAPPA-GANs for Parallel MRI Reconstruction. https://arxiv.org/abs/2101.03135

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