Parallel Compressed Sensing MRI using Reweighted L1 Minimization

Ching-Hua Chang¹, Jim Ji¹

The combination of Compressed Sensing (CS) with multiple receiver coils has drawn great attentions because of their potentials to significantly reduce acquisition time in MRI. The former emerged by exploring the sparsity of MR images, and the latter can reduce scan time by resorting to parallel MRI (pMRI). CS can be used as regularization method and is integrated to take advantages of the sensitivity information from multiple receiver coils. In this abstract, we propose to use a reweighted nonlinear conjugate gradient L1 minimization method to enhance the reconstruction of parallel CS-MRI.