M. Golbabaee, D. Chen, PA. Gómez, MI. Menzel, M.E. Davies A deep learning approach for magnetic resonance fingerprinting international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques (iTWIST), Aalborg, Denmark, August 2018 (bib)
	Current popular methods for Magnetic Resonance Fingerprint (MRF) recovery are bottlenecked by the heavy storage and computation requirements of a matched-filtering step due to the growing size and complexity of the fingerprint dictionaries in multi-parametric quantitative MRI applications. In this abstract we investigate and evaluate advantages of a deep learning approach for embedding the manifold of solutions of the Bloch equations and to address these shortcomings.
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