Sequence adaptive field-imperfection estimation (SAFE): retrospective estimation and correction of and inhomogeneities for enhanced MRF quantification
arXiv:2312.09488
Abstract
and field-inhomogeneities can significantly reduce accuracy and robustness of MRF's quantitative parameter estimates. Additional and calibration scans can mitigate this but add scan time and cannot be applied retrospectively to previously collected data. Here, we proposed a calibration-free sequence-adaptive deep-learning framework, to estimate and correct for and effects of any MRF sequence. We demonstrate its capability on arbitrary MRF sequences at 3T, where no training data were previously obtained. 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.
12 pages, 5 figures, submitted to International Society for Magnetic Resonance in Medicine 31th Scientific Meeting, 2024