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Abstract #0251

3D magnetic resonance fingerprinting with a clustered spatiotemporal dictionary

Pedro A. Gómez1,2, Guido Buonincontri3, Miguel Molina-Romero1,2, Cagdas Ulas1,2, Jonatahn I. Sperl2, Marion I. Menzel2, and Bjoern H. Menze1

1Technische Universität München, Garching, Germany, 2GE Global Research, Garching, Germany, 3Istituto Nazionale di Fisica Nucleare, Pisa, Italy

We present a method for creating a spatiotemporal dictionary for magnetic resonance fingerprinting (MRF). Our technique is based on the clustering of multi-parametric spatial kernels from training data and the posterior simulation of a temporal fingerprint for each voxel in every cluster. We show that the parametric maps estimated with a clustered dictionary agree with maps estimated with a full dictionary, and are also robust to undersampling and shorter sequences, leading to increased efficiency in parameter mapping with MRF.

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