Magnetic resonance fingerprinting, Nature, vol.495, issue.7440, p.187, 2013. ,
Magnetic resonance fingerprinting: a technical review, Magnetic resonance in medicine, vol.81, issue.1, pp.25-46, 2019. ,
MR vascular fingerprinting: a new approach to compute cerebral blood volume, mean vessel radius, and oxygenation maps in the human brain, Neuroimage, vol.89, pp.262-270, 2014. ,
SVD compression for magnetic resonance fingerprinting in the time domain, IEEE transactions on medical imaging, vol.33, issue.12, pp.2311-2322, 2014. ,
Fast group matching for MR fingerprinting reconstruction, Magnetic resonance in medicine, vol.74, issue.2, pp.523-528, 2015. ,
Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling, Magnetic resonance in medicine, vol.79, issue.2, pp.933-942, 2018. ,
Low rank approximation methods for MR fingerprinting with large scale dictionaries, Magnetic resonance in medicine, vol.79, issue.4, pp.2392-2400, 2018. ,
Low rank alternating direction method of multipliers reconstruction for mr fingerprinting, Magnetic resonance in medicine, vol.79, issue.1, pp.83-96, 2018. ,
Dictionary-free MRI perk: Parameter estimation via regression with kernels, IEEE transactions on medical imaging, vol.37, issue.9, pp.2103-2114, 2018. ,
Maximum likelihood reconstruction for magnetic resonance fingerprinting, IEEE transactions on medical imaging, vol.35, issue.8, pp.1812-1823, 2016. ,
Better than real: Complex-valued neural nets for MRI fingerprinting, 2017 IEEE International Conference on Image Processing (ICIP), pp.3953-3957, 2017. ,
Deep learning for magnetic resonance fingerprinting: A new approach for predicting quantitative parameter values from time series, Stud Health Technol Inform, vol.243, pp.202-206, 2017. ,
Rinq fingerprinting: Recurrence-informed quantile networks for magnetic resonance fingerprinting, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.92-100, 2019. ,
MR fingerprinting deep reconstruction network (drone), Magnetic resonance in medicine, vol.80, issue.3, pp.885-894, 2018. ,
Magnetic resonance fingerprinting reconstruction via spatiotemporal convolutional neural networks, International Workshop on Machine Learning for Medical Image Reconstruction, pp.39-46, 2018. ,
Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach, 2018. ,
Hydra: Hybrid deep magnetic resonance fingerprinting, Medical physics, vol.46, issue.11, pp.4951-4969, 2019. ,
Geometry of deep learning for magnetic resonance fingerprinting, ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.7825-7829, 2019. ,
Dictionary-free MR fingerprinting parameter estimation via inverse regression, 26th Annual Meeting ISMRM, p.4259, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01941630
High-dimensional regression with Gaussian mixtures and partially-latent response variables, Statistics and Computing, vol.25, issue.5, pp.893-911, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-00863468
Sliced Inverse Regression for dimension reduction, Journal of the American Statistical Association, vol.86, issue.414, pp.316-327, 1991. ,
Partial least squares prediction in high-dimensional regression, Ann. Statist, vol.47, issue.2, p.2019 ,
Approximation results regarding the multipleoutput Gaussian gated mixture of linear experts model, Neurocomputing, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02265793
Local statistical modeling via a cluster-weighted approach with elliptical distributions, Journal of Classification, vol.29, pp.363-401, 2012. ,
Random number generation and quasi-Monte Carlo methods, vol.63, 1992. ,
Randomly permuted (t, m, s)-nets and (t, s)-sequences," in Monte Carlo and quasi-Monte Carlo methods in scientific computing, pp.299-317, 1995. ,
Algorithm 659: Implementing sobol's quasirandom sequence generator, ACM Transactions on Mathematical Software (TOMS), vol.14, issue.1, pp.88-100, 1988. ,
On the l 2 -discrepancy for anchored boxes, Journal of Complexity, vol.14, issue.4, pp.527-556, 1998. ,
A simulation tool for dynamic contrast enhanced MRI, PloS one, vol.8, issue.3, p.57636, 2013. ,
URL : https://hal.archives-ouvertes.fr/inserm-00861236
MR vascular fingerprinting in stroke and brain tumors models, Scientific reports, vol.6, p.37071, 2016. ,
Vessel size imaging, Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, vol.45, issue.3, pp.397-408, 2001. ,
Imaging the microvessel caliber and density: principles and applications of microvascular MRI, Magnetic resonance in medicine, vol.73, issue.1, pp.325-341, 2015. ,
Evaluation of the relationship between MR estimates of blood oxygen saturation and hypoxia: effect of an antiangiogenic treatment on a gliosarcoma model, Radiology, vol.265, issue.3, pp.743-752, 2012. ,
Information theory and an extension of the maximum likelihood principle, pp.199-213, 1998. ,
Estimating the dimension of a model, The annals of statistics, vol.6, issue.2, pp.461-464, 1978. ,
Fully automatic lesion localization and characterization: Application to brain tumors using multiparametric quantitative MRI data, IEEE transactions on medical imaging, vol.37, issue.7, pp.1678-1689, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01545548
Animal research: reporting in vivo experiments: the arrive guidelines, British journal of pharmacology, vol.160, issue.7, pp.1577-1579, 2010. ,