Sequence Adaptive B1+ and B0 Field-imperfections Estimation (SAFE) for enhanced MRF quantification

Motivation: B1+ and B0 field-inhomogeneities can significantly reduce accuracy and robustness of MRF’s quantitative parameter estimates. Additional B1+ and B0 calibration scans can mitigate this but add scan time and cannot be applied retrospectively to previously collected data. Goal(s): Here, we proposed a calibration-free sequence-adaptive deep-learning framework, to estimate and correct for B1+ and B0 effects of any MRF sequence. Approach: We demonstrate its capability on arbitrary MRF sequences at 3T, where no training data were previously obtained. Results: Such approach can be applied to any previously-acquired and future MRF-scans. The flexibility in directly applying this framework to other quantitative sequences is also highlighted. Impact: Proposed method can estimate B1+ and B0 maps without calibration scan and be applied to arbitrary MRF sequence without new training data. It can be used retrospectively to improve quality of parameter maps of any previously-acquired or future MRF data.