Magnetic resonance fingerprinting (MRF) quantifies various properties simultaneously by matching measurements to a dictionary of precomputed signals. We propose to extend the MRF framework by using a database to introduce additional parameters and spatial characteristics to the dictionary. We show that, with an adequate matching technique which includes an update in parameter space, it is possible to recon- struct parametric maps, synthesize modalities, and label tissue types at the same time directly from an MRF acquisition. We compare (1) relaxation maps from a spatiotemporal dictionary against a temporal MRF dictionary, (2) synthetic diffusion metrics versus those obtained with a standard diffusion acquisition, and (3) anatomical labels generated from MRF signals to an established segmentation method, demonstrating the potential of using MRF for multiparametric brain mapping.
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Magnetic resonance fingerprinting (MRF) quantifies various properties simultaneously by matching measurements to a dictionary of precomputed signals. We propose to extend the MRF framework by using a database to introduce additional parameters and spatial characteristics to the dictionary. We show that, with an adequate matching technique which includes an update in parameter space, it is possible to recon- struct parametric maps, synthesize modalities, and label tissue types at the same time di...
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