Field-Correcting GRAPPA (FCG) for improved mitigation of even-odd and field-related artifacts in EPI

Motivation: Field perturbation from gradient error and eddy current has been a long-standing issue for EPI, especially with high gradient performance or ramp samplingGoal(s): To develop a MLP based Field-Correcting GRAPPA (FCG) that accounts for spatial-varying field and produces artifacts-mitigated imagesApproach: Calibration data with dual polarity were acquired. A MLP based kernel was trained to take single-polarity data as input and output the clean averaged data. It was applied for both phantom and in vivo undersampled EPI with ramp-sampling. Results: FCG produced best correction results for ramp-sampling EPI, with potentials for wide applications including fMRI. Impact: A Field-Correcting GRAPPA (FCG) technique was developed to correct the field perturbation induced image artifacts for EPI, which accounts for spatial varying field and produced promising resulting on ramp-sampling cases, with great potentials for wide applications including fMRI.