83 citations · 141 across the 10 of their papers we have counts for
13 papers
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…
vol2Brain: A new online Pipeline for whole Brain MRI analysis
Jose V. Manjon, Jose E. Romero, Roberto Vivo-Hernando +4
Automatic and reliable quantitative tools for MR brain image analysis are a very valuable resources for both clinical and research environments. In the last years, this field has e…
Deep correction of breathing-related artifacts in real-time MR-thermometry
Baudouin Denis de Senneville, Pierrick Coupé, Mario Ries +2
Real-time MR-imaging has been clinically adapted for monitoring thermal therapies since it can provide on-the-fly temperature maps simultaneously with anatomical information. Howev…
Accuracy of MRI Classification Algorithms in a Tertiary Memory Center Clinical Routine Cohort
Alexandre Morin, Jorge Samper-González, Anne Bertrand +12
BACKGROUND:Automated volumetry software (AVS) has recently become widely available to neuroradiologists. MRI volumetry with AVS may support the diagnosis of dementias by identifyin…
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.…