Singular value decomposition (SVD) and view-sharing compression can decrease the size of the dictionary without compromising accuracy in magnetic resonance fingerprinting (MRF). While the latter accounts for the B1+ of multiple transmit channels in the dictionary, the SVD compression scheme was designed for single-channel transmission. In this work we extended SVD-based fingerprint compression to the case of two or more independent RF sources and evaluated its performance in simulation. We showed that accurate parametric maps can be achieved using only six SVD components, both in fully-sampled and highly under-sampled MRF experiments. Future work will include optimization of k-space under-sampling.
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