TV-RSPIRiT:Total Variation Regularized Based Robust Self-Consistent Parallel Imaging Reconstruction

摘要

RSPIRIT is a magnetic resonance imaging method based on generalized Lasso that is more robust than SPIRiT in terms of calibration errors, but often suffers from noise. In this study, we present TV-RSPRiT that can generate higher signal-to-noise images through total variation regularization. The model contains two non-smooth problems that solved using first order primal dual algorithm. Comparisons with several recent parallel imaging algorithms indicate that the proposed method significantly improves the quality of reconstruction images