MR vascular fingerprinting aims at mapping cerebral vascular properties. We propose to improve the method on two levels: (1) by testing new acquisitions patterns using a Monte-Carlo based method that assesses the encoding capacity of MRF sequences; and (2) by testing new geometrical models that represent vascular networks during dictionary simulations. We obtained results suggesting that new MRF-type sequences can be tailored for vascular exploration and should be tested in vivo. We also showed the clear influence of geometry in the simulations and the possibility to include realistic vascular networks.
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