A Hybrid Sampling Strategy for Sparse Magnetic Resonance Imaging

A hybrid acquisition sequence for Sparse 2D Magnetic Resonance Imaging (MRI) is presented. The method combines random sampling of Cartesian trajectories with an adaptive 2D acquisition of radial projections. It is based on the evaluation of the information content of a small percentage of the k-space data collected randomly, to identify radial blades of k-space coefficients having maximum information content. An entropy function is defined on the power spectrum of the projections for evaluating the information content of each direction. The method has been tested on MRI images and it was also compared to the weighted Compressed Sensing. Some results are reported and discussed.