Inspired 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.
Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Jessica Prisciandaro, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Arvind Shah, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso
Ahmed Bassam Sayed Ayoub Mohamed Emam