Magnetic Resonance Fingerprinting (MRF) is an accelerated acquisition and reconstruction method employed to generate multiple parametric maps. Tailored MRF (TMRF) coupled with deep learning based reconstruction has been proposed to overcome the shortcoming of T2 under estimation and the need for dictionaries respectively. A generalized approach with training of natural images and a specific approach with training of brain data are detailed in this work. Both approaches are demonstrated, compared and quantified.
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