, Recherche-10-IA Institut Hospitalo-Universitaire-6)
, Recherche-11-Initiative d'Excellence-004, project LearnPETMR number SU-16-R-EMR-16), and from the
Multiple sclerosis, Lancet, vol.372, issue.9648, pp.1502-1517, 2008. ,
URL : https://hal.archives-ouvertes.fr/hal-00996686
MRI in the diagnosis of MS: a prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT, Neurology, vol.38, pp.180-185, 1988. ,
Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis, Brain, vol.120, pp.2059-2069, 1997. ,
Detection of simulated multiple sclerosis lesions on t2-weighted and flair images of the brain: Observer performance, Radiology, vol.241, issue.1, pp.206-212, 2006. ,
The alzheimer's disease neuroimaging initiative, Neuroimaging clinics of North America, vol.15, p.869, 2005. ,
Is synthesizing mri contrast useful for intermodality analysis?, Medical Image Computing and Computer-Assisted InterventionMICCAI 2013, vol.8149, 2013. ,
Why does synthesized data improve multi-sequence classification?, Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015, vol.9349, 2015. ,
MR contrast synthesis for lesion segmentation, Proc IEEE Int Symp Biomed Imaging, pp.932-935, 2010. ,
Random Forest FLAIR Reconstruction from T1, T2, and PD-Weighted MRI, Proc IEEE Int Symp Biomed Imaging, pp.1079-1082, 2014. ,
Estimating CT Image From MRI Data Using Structured Random Forest and Auto-Context Model, IEEE Trans Med Imaging, vol.35, issue.1, pp.174-183, 2016. ,
Attenuation correction synthesis for hybrid pet-mr scanners: Application to brain studies, IEEE Transactions on Medical Imaging, vol.33, issue.12, pp.2332-2341, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-01827217
Deep residual learning for image recognition, 2016 IEEE Conference on CVPR, pp.770-778, 2016. ,
Learning efficient object detection models with knowledge distillation, Advances in Neural Information Processing Systems, vol.30 ,
, , pp.742-751, 2017.
Fully convolutional networks for semantic segmentation, IEEE Trans. Pattern Anal. Mach. Intell, vol.39, issue.4, pp.640-651, 2017. ,
Deep Learning for Medical Image Analysis, 2017. ,
Convolutional neural network for reconstruction of 7t-like images from 3t mri using appearance and anatomical features, Deep Learning and Data Labeling for Medical Applications, LABELS 2016, vol.10008, 2016. ,
Estimating ct image from mri data using 3d fully convolutional networks, Deep Learning and Data Labeling for Medical Applications-LABELS 2016, vol.10008, pp.170-178, 2016. ,
Deep learning based imaging data completion for improved brain disease diagnosis, Medical Image Computing and Computer-Assisted Intervention-MICCAI 2014, vol.8675, pp.305-312, 2014. ,
Whole image synthesis using a deep encoder-decoder network, Simulation and Synthesis in Medical Imaging, vol.9968, pp.127-137, 2016. ,
Backpropagation applied to handwritten zip code recognition, Neural Comput, vol.1, pp.541-551, 1989. ,
Imagenet classification with deep convolutional neural networks, NIPS 25, pp.1097-1105, 2012. ,
Deep inside convolutional networks: Visualising image classification models and saliency maps, 2013. ,
N4itk: Improved n3 bias correction, IEEE Transactions on Medical Imaging, vol.29, pp.1310-1320, 2010. ,
Accurate and robust brain image alignment using boundary-based registration, NeuroImage, vol.48, issue.1, pp.63-72, 2009. ,
Theano: A Python framework for fast computation of mathematical expressions, 2016. ,
Keras, 2015. ,
Modality propagation: Coherent synthesis of subjectspecific scans with data-driven regularization, Medical Image Computing and ComputerAssisted Intervention-MICCAI 2013, vol.8149, 2013. ,
U-net: Convolutional networks for biomedical image segmentation, Medical Image Computing and Computer-Assisted Intervention (MICCAI), vol.9351, pp.234-241, 2015. ,
Lesionbrain: An online tool for white matter lesion segmentation, International Workshop on Patch-based Techniques in Medical ImagingPatch-MI 2018, 2018. ,
Image-to-image translation with conditional adversarial networks, 2016. ,
, Differential diagnosis of neurode