Location constrained approximate message passing for compressed sensing MRI. Issue 2 (5th October 2012) - Sung, Kyunghyun; Daniel, Bruce L.; Hargreaves, Brian A.
<x xml:space="preserve">Abstract</x> Iterative thresholding methods have been extensively studied as faster alternatives to convex optimization methods for solving large‐sized problems in compressed sensing. A novel iterative thresholding method called LCAMP (Location Constrained Approximate Message Passing) is presented for reducing computational complexity and improving reconstruction accuracy when a nonzero location (or sparse support) constraint can be obtained from view shared images. LCAMP modifies the existing approximate message passing algorithm by replacing the thresholding stage with a location constraint, which avoids adjusting regularization parameters or thresholding levels. This work is first compared with other conventional reconstruction methods using random one‐dimention signals and then applied to dynamic contrast‐enhanced breast magnetic resonance imaging to demonstrate the excellent reconstruction accuracy (less than 2% absolute difference) and low computation time (5–10 s using Matlab) with highly undersampled three‐dimentional data (244 × 128 × 48; overall reduction factor = 10). Magn Reson Med 70:370–381, 2013. © 2012 Wiley Periodicals, Inc.