Magnetic Resonance Fingerprinting (MRF) provides simultaneous multi-parametric maps from a continuous transient state acquisition of many time-point images. Motion occurring during the MRF acquisition can create artefacts in the consequent T1/T2 maps. Here we propose to derive an intermediate 1D motion model from the acquired MRF data itself via self-navigation of the k-space central point and further refine the motion estimates using an autofocus algorithm for MRF motion correction. The proposed approach was evaluated in simulations.
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