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Magnetic resonance fingerprinting methods quantify multiple MR parameters by matching the measured signal to a precomputed 5-dimensional dictionary in which each parameter is a dimension. Generating high-precision maps requires dense grids in each dimension, which is prohibitively expensive in memory and computation time. 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 method is shown to substantially reduce fitting error.
This presentation is part of Minisymposium “MS47 - Splines in Imaging (3 parts)”
organized by: Carolina Beccari (Dept. Mathematics, University of Bologna) , Virginie Uhlmann (EPFL, Lausanne) , Michael Unser (EPFL, Lausanne) .