An Augmented Lagrangian Method for MR Coil Sensitivity Estimation

Michael John Allison¹, Jeffrey A. Fessler¹

Accurate coil sensitivity estimates are required to avoid artifacts in many parallel imaging techniques. Existing regularized methods provide sufficiently accurate estimates, but often at a high computational cost. We propose an iterative technique that uses Augmented Lagrangian principles to efficiently compute sensitivity estimates. Our method generated sensitivity estimates for a challenging breast phantom dataset in half the time required by a conjugate gradient algorithm. We therefore conclude that our AL approach provides an efficient strategy for accurately estimating coil sensitivities.