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Abstract #2713

Simplified Iterative GRAPPA for Fast and Robust Parallel MRI with Arbitrary Trajectories

Martin Blaimer1, Andr Fischer1, Philipp Ehses2, Nicole Seiberlich3, Mark A. Griswold3, Peter M. Jakob1,2, Felix A. Breuer1

1Research Center Magnetic Resonance Bavaria (MRB), Wrzburg, Bavaria, Germany; 2Department of Experimental Physics 5, University of Wrzburg, Wrzburg, Bavaria, Germany; 3Department of Radiology, University Hospitals of Cleveland and Case Western Reserve University, Cleveland, OH, USA

Generalized solutions for parallel MRI using arbitrary k-space trajectories are mainly based on iterative algorithms, such as conjugate gradient SENSE. In addition, an iterative GRAPPA approach for arbitrary k-space sampling has been presented. However, the reconstruction process includes several steps, including gridding, GRAPPA convolution and re-sampling operations during each iteration. Here, we present a simplified iterative GRAPPA algorithm. The key element is a GRAPPA-operator gridding (GROG) step prior to the iteration loop which removes the need for gridding and resampling during each iteration. This allows a robust and computationally efficient reconstruction of accelerated non-Cartesian MRI experiments.