A Method to Combine Compressed Sensing with Auto-Calibrating Parallel Imaging Reconstruction for Cartesian Acquisition

Kang Wang¹, Philip Beatty², James Holmes², Reed Busse², Jean Brittain², Frank Korosec¹

This abstract presents a framework that combines compressed sensing (CS) with auto-calibration parallel imaging (acPI) reconstruction for undersampled Cartesian acquisition. In data acquisition, a two-step undersampling scheme is used. For reconstruction, an acPI method is integrated into the CS L1 norm minimization process, such that both the coherent and incoherent aliasing artifacts associated with the undersampling can be suppressed in the iteration. The feasibility of the new method was validated using 3D contrast-enhanced peripheral MR angiography data sets