Non-Cartesian Parallel Imaging Reconstruction using PRUNO-GROG

Jian Zhang¹, Ajit Shankaranarayanan²

Pseudo-Cartesian GRAPPA in conjunction with GROG (PCG-GROG) is an effective algorithm to reconstruct non-Cartesian parallel imaging data. However, the PCG reconstruction is usually a cumbersome task as different fitting patterns need to be determined point by point. PRUNO is a generalized auto-calibrated reconstruction algorithm, in which local ing kernels are independent of the acceleration factor and undersampling patterns. We can thus replace the PCG step with PRUNO to bring out a more convenient and accurate algorithm, termed PRUNO-GROG. Promising preliminary results are shown on both phantom and in vivo images.