83 citations · 112 across the 6 of their papers we have counts for
5 papers · 1 filter
Deep Grading based on Collective Artificial Intelligence for AD Diagnosis and Prognosis
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal +1
Accurate diagnosis and prognosis of Alzheimer's disease are crucial to develop new therapies and reduce the associated costs. Recently, with the advances of convolutional neural ne…
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.…