Davies, MikePuy, GillesVandergheynst, PierreWiaux, Yves2014-02-062014-02-062014-02-06201410.1109/ICASSP.2014.6854937https://infoscience.epfl.ch/handle/20.500.14299/1004171312.2457Inspired by the recently proposed Magnetic Resonance Fin- gerprinting technique, we develop a principled compressed sensing framework for quantitative MRI. The three key com- ponents are: a random pulse excitation sequence following the MRF technique; a random EPI subsampling strategy and an iterative projection algorithm that imposes consistency with the Bloch equations. We show that, as long as the ex- citation sequence possesses an appropriate form of persistent excitation, we are able to achieve accurate recovery of the proton density, T1, T2 and off-resonance maps simultane- ously from a limited number of samples.compressed sensingMRIBloch equationsmanifoldsJohnston-Linderstrauss embeddingstext::conference output::conference proceedings::conference paper