title: Spread spectrum magnetic resonance imaging.
abstract: We propose a novel compressed sensing technique to accelerate the magnetic resonance imaging (MRI) acquisition process. The method, coined spread spectrum MRI or simply s(2)MRI, consists of premodulating the signal of interest by a linear chirp before random k-space under-sampling, and then reconstructing the signal with nonlinear algorithms that promote sparsity. The effectiveness of the procedure is theoretically underpinned by the optimization of the coherence between the sparsity and sensing bases. The proposed technique is thoroughly studied by means of numerical simulations, as well as phantom and in vivo experiments on a 7T scanner. Our results suggest that s(2)MRI performs better than state-of-the-art variable density k-space under-sampling approaches.
authors: Institute of Electrical Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. gilles.puy@epfl.ch
authors: Gilles
authors: G
authors: Puy
authors: Jose P
authors: JP
authors: Marques
authors: Rolf
authors: R
authors: Gruetter
authors: Jean-Philippe
authors: JP
authors: Thiran
authors: Dimitri
authors: D
authors: Van De Ville
authors: Pierre
authors: P
authors: Vandergheynst
authors: Yves
authors: Y
authors: Wiaux
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D017711:Nonlinear Dynamics; D019047:Phantoms, Imaging; D015203:Reproducibility of Results