Kyunghyun Sung1, Bruce L. Daniel1, Brian A. Hargreaves1
Iterative thresholding methods have been extensively studied as faster alternatives to convex optimization for large-sized problems in compressed sensing (CS). A common large-sized problem is dynamic contrast enhanced (DCE) MRI, and the dynamic measurements possess data redundancies, which can be used to estimate non-zero signal locations. In this work, we present a novel iterative thresholding method called LCAMP (Location Constrained Approximate Message Passing) by adding the non-zero location assumption and an approximate message passing term. The method can reduce computational complexity and improve reconstruction accuracy.