37 citations · 64 across the 4 of their papers we have counts for
6 papers · 1 filter
DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentation
Reda Abdellah Kamraoui, Vinh-Thong Ta, Thomas Tourdias +3
Recently, segmentation methods based on Convolutional Neural Networks (CNNs) showed promising performance in automatic Multiple Sclerosis (MS) lesions segmentation. These technique…
RegQCNET: Deep Quality Control for Image-to-template Brain MRI Affine Registration
Baudouin Denis de Senneville, José V. Manjon, Pierrick Coupé
Affine registration of one or several brain image(s) onto a common reference space is a necessary prerequisite for many image processing tasks, such as brain segmentation or functi…
AssemblyNet: A large ensemble of CNNs for 3D Whole Brain MRI Segmentation
Pierrick Coupé, Boris Mansencal, Michaël Clément +5
Whole brain segmentation using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images.…
MRI denoising using Deep Learning and Non-local averaging
Jose V. Manjon, Pierrick Coupe
This paper proposes a novel method for automatic MRI denoising that exploits last advances in deep learning feature regression and self-similarity properties of the MR images. The…
Multi-scale Graph-based Grading for Alzheimer's Disease Prediction
Kilian Hett, Vinh-Thong Ta, José V. Manjón +1
The prediction of subjects with mild cognitive impairment (MCI) who will progress to Alzheimer's disease (AD) is clinically relevant, and may above all have a significant impact on…
AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
Pierrick Coupé, Boris Mansencal, Michaël Clément +5
Whole brain segmentation using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images.…