A compressive hybrid conjugate gradient image recovery approach for radial MRI

This paper investigates an efficient compressed sensing (CS) approach that can be used to reconstruct radial magnetic resonance (MR) images from under-sampled measurements. In this approach, we propose a hybrid conjugate gradient (CG) method with a hybrid update parameter to optimize the CS cost function. With detailed mathematical proofs, the proposed CG method has proved to have sufficient descent and global convergence properties. In order to...