Parallel MRI reconstruction by convex optimization

The thesis provides a novel approach to parallel Magnetic Resonance Imaging (MRI) reconstruction. It will significantly make contributions in two cases for parallel MRI reconstruction. Firstly, it reconstructs a true optimal solution by convex optimization for the reconstructed MR image which provides improved mean square error performance over other state-of-art methods. Then, it will allow to decrease the parallel MRI scanning time due to it's improved efficiency enabling to scan lower number of samples during MRI data acquisition.