Haris Saybasili1, J. Andrew Derbyshire1, Liheng Guo2, Ozan Sayin2, Annette M. Stine1, Robert J. Lederman1, Daniel A. Herzka2
1National Heart Lung & Blood Institute, National Institutes of Health, Bethesda, MD, United States; 2Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, United States
This work describes a fully auto-calibrated GRAPPA approach for the reconstruction of Golden-step Cartesian MRI data. Golden-step Cartesian MRI advances the phase encoding gradients in steps of the golden fraction of the k-space support region. The resulting data sets are non-uniformly sampled in the phase encode direction and have advantageous properties for real-time imaging, permiting arbitrary and retrospective selection of temporal resolution, FOV and parallel imaging acceleration rate. In our approach the Golden-step MRI data are mapped onto the nearest Cartesian grid position using 1D SC-GROG. GRAPPA is then applied to estimate missing lines prior to a standard FFT reconstruction.