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Regularized parallel mri reconstruction using an alternating direction method of multipliers
2011
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Using sparsity-based regularization to improve magnetic resonance image (MRI) reconstruction quality demands computation-intensive nonlinear optimization. In this paper, we develop an iterative algorithm based on the method of multipliers-augmented Lagrangian (AL) formalism-for reconstruction from sensitivity encoded data using sparsity-based regularization. We first convert the unconstrained reconstruction problem into an equivalent constrained optimization task and attack the constrained
doi:10.1109/isbi.2011.5872429
dblp:conf/isbi/RamaniF11
fatcat:bytyzbutzbbdvoeszbg6iouupq