Variable density compressed sensing in MRI. Theoretical vs heuristic sampling strategies, 2013 IEEE 10th International Symposium on Biomedical Imaging, pp.298-301, 2013. ,
DOI : 10.1109/ISBI.2013.6556471
URL : https://hal.archives-ouvertes.fr/hal-00848271
A Projection Algorithm for Gradient Waveforms Design in Magnetic Resonance Imaging, IEEE Transactions on Medical Imaging, vol.35, issue.9, pp.2026-2039 ,
DOI : 10.1109/TMI.2016.2544251
URL : https://hal.archives-ouvertes.fr/hal-01317939
XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing, Magnetic Resonance in Medicine, vol.266, issue.2008, pp.775-788, 2016. ,
DOI : 10.1148/radiol.12120826
Using NFFT 3---A Software Library for Various Nonequispaced Fast Fourier Transforms, ACM Transactions on Mathematical Software, vol.36, issue.4, p.19, 2009. ,
DOI : 10.1145/1555386.1555388
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.3705
SPARKLING : Novel non- Cartesian sampling schemes for accelerated 2D anatomical imaging at 7T using compressed sensing, Proceedings 25th Scientific Meeting, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01577200
Sparse MRI: The application of compressed sensing for rapid MR imaging, Magnetic Resonance in Medicine, vol.170, issue.6, pp.1182-1195, 2007. ,
DOI : 10.1002/mrm.21391
Compressed Sensing MRI, IEEE Signal Processing Magazine, vol.25, issue.2, pp.72-82, 2008. ,
DOI : 10.1109/MSP.2007.914728
On Variable Density Compressive Sampling, IEEE Signal Processing Letters, vol.18, issue.10, pp.595-598, 2011. ,
DOI : 10.1109/LSP.2011.2163712
URL : http://arxiv.org/pdf/1109.6202
Motion corrected compressed sensing for free-breathing dynamic cardiac MRI, Magnetic Resonance in Medicine, vol.18, issue.2, pp.504-516, 2013. ,
DOI : 10.1109/42.774166
URL : https://kclpure.kcl.ac.uk/portal/files/9664401/mrm24463.pdf
Clinical applications of 7T MRI in the brain, European Journal of Radiology, vol.82, issue.5, pp.708-718, 2013. ,
DOI : 10.1016/j.ejrad.2011.07.007
Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004. ,
DOI : 10.1109/TIP.2003.819861
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.2477