Evaluation of Conjugate-Gradient Phase Correction Algorithm under Noisy Conditions
Zhang J, Liu C, Moseley M
Stanford University, Stanford University
SNAILS image reconstruction algorithm is adapted from SENSE using CG method, by treating the phase correction map of each interleaf as coil sensitivity. However, little is known about the performance of the algorithm under noisy conditions with a worse conditioned encoding matrix. We evaluate the algorithm on simulated SNAILS data with various degrees of motion-induced phase error and a wide range of noise level. It is shown that the iterative CG method corrects phase errors effectively. It does successful reconstructions even at low SNRs.