HYPR-L0: a Hybrid Technique for CE MRA with Extreme Data Undersampling Factors

Julia V. Velikina¹, Alexey A. Samsonov

We present a novel synergistic method for time-resolved image reconstruction from extremely undersampled data that utilizes independent acceleration mechanisms of non-Cartesian acquisition, parallel imaging, compressed sensing, and HYPR. The new technique is validated for applications to time-resolved contrast-enhanced angiography of the brain where it produces images with high spatial and temporal resolution and high SNR for the acceleration factors at which other reconstruction methods fail.