Dictionary matching in MR fingerprinting acquisitions quantifying many parameters, such as T1 T2, T2’, B0, B1+, and PD, becomes prohibitively expensive due to the dense grid in each dimension of the dictionary that is required. In this work we propose B-spline interpolation of the dictionary to reduce the dictionary size and to enable efficient nonlinear least-squares fitting by gradient-based optimization methods. The experiments show that the method substantially reduces fitting error, especially when the SNR is high and dictionary resolution is the limiting factor for improving the precision of the quantitative parameters.
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