Magnetic Resonance Fingerprinting (MRF) maps multiple tissue properties and system parameters simultaneously. The accuracy of MRF maps depends on the simulation of all possible system properties into the signal evolutions via the Bloch equations. We have observed frequency drifts during MRF scans, similar to those seen in fMRI scans, which might cause various artifacts if not accounted for. Here, it is shown that 2D MRF frequency drifts can be compensated with a simple dictionary update. For correction of 3D MRF frequency drifts, a novel reconstruction framework is introduced. Results show significant improvements on quantitative maps for 2D and 3D MRF.
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