Keywords: MR Fingerprinting/Synthetic MR, Sparse & Low-Rank ModelsWe propose an iterative algorithm to remove remaining artefacts of Magnetic Resonance Fingerprinting maps, using projected gradient descent with exact line search and spatial regularization. We use this framework to denoise 3D MRF T1-FF acquisitions undersampled in the partition direction and show that this allows to reduce undersampling artefacts for the T1H2O and FF maps after a few iterations.
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