Gilles Puy tweeted about the release of the Spread spectrum MRI toolbox. From the page:
Spread spectrum magnetic resonance imaging - s2MRI
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 s2MRI, consists of pre-modulating the signal of interest by a linear chirp before random k-space under-sampling, and then reconstructing the signal with non-linear 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 s2MRI performs better than state-of-the-art variable density k-space under-sampling approaches.
If you use this toolbox, please cite the following paper: Spread spectrum magnetic resonance imaging," IEEE Transactions on Medical Imaging, vol. 31(3), pp. 586 - 598, 2012.
Comments: gilles {DOT} puy {AT} epfl {DOT} ch
Image Credit: NASA/JPL-Caltech
This image was taken by Navcam: Right A (NAV_RIGHT_A) onboard NASA's Mars rover Curiosity on Sol 17 (2012-08-23 17:18:51 UTC) .
Full Resolution
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.
No comments:
Post a Comment