Abstract #0251

3D magnetic resonance fingerprinting with a clustered spatiotemporal dictionary

Pedro A. Gómez^1,2, Guido Buonincontri³, Miguel Molina-Romero^1,2, Cagdas Ulas^1,2, 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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