Magnetic resonance fingerprinting is a framework for creating quantitative tissue property maps from a single acquisition. The accuracy and precision of these maps depend upon a precomputed dictionary of simulated signal evolutions, to which acquired signals are matched using the inner product to determine the tissue property values. We propose to approximate the inner product as a quadratic function of the tissue properties in a neighborhood around the correct match in order to reduce the effect of tissue property step size in the dictionary. Results from data acquired with different MRF sequences demonstrate the value of the proposed approach.
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