37 citations · 62 across the 3 of their papers we have counts for
6 papers
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…
DeepHIPS: A novel Deep Learning based Hippocampus Subfield Segmentation method
Jose V. Manjon, Jose E. Romero, Pierrick Coupe
The automatic assessment of hippocampus volume is an important tool in the study of several neurodegenerative diseases such as Alzheimer's disease. Specifically, the measurement of…
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.…