4 citations · 10 across the 7 of their papers we have counts for
7 papers
NC-Reg : Neural Cortical Maps for Rigid Registration
Ines Vati, Pierrick Bourgeat, Rodrigo Santa Cruz +4
We introduce neural cortical maps, a continuous and compact neural representation for cortical feature maps, as an alternative to traditional discrete structures such as grids and…
CorticalFlow: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability
Rodrigo Santa Cruz, Léo Lebrat, Darren Fu +4
The problem of Cortical Surface Reconstruction from magnetic resonance imaging has been traditionally addressed using lengthy pipelines of image processing techniques like FreeSurf…
CorticalFlow: A Diffeomorphic Mesh Deformation Module for Cortical Surface Reconstruction
Léo Lebrat, Rodrigo Santa Cruz, Frédéric de Gournay +5
In this paper we introduce CorticalFlow, a new geometric deep-learning model that, given a 3-dimensional image, learns to deform a reference template towards a targeted object. To…
DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction
Rodrigo Santa Cruz, Leo Lebrat, Pierrick Bourgeat +3
The study of neurodegenerative diseases relies on the reconstruction and analysis of the brain cortex from magnetic resonance imaging (MRI). Traditional frameworks for this task li…
Going deeper with brain morphometry using neural networks
Rodrigo Santa Cruz, Léo Lebrat, Pierrick Bourgeat +5
Brain morphometry from magnetic resonance imaging (MRI) is a consolidated biomarker for many neurodegenerative diseases. Recent advances in this domain indicate that deep convoluti…
Bayesian Modeling of Multiple Structural Connectivity Networks During the Progression of Alzheimer's Disease
Christine B. Peterson, Nathan Osborne, Francesco C. Stingo +3
Alzheimer's disease is the most common neurodegenerative disease. The aim of this study is to infer structural changes in brain connectivity resulting from disease progression usin…
Enforcing temporal consistency in Deep Learning segmentation of brain MR images
Malav Bateriwala, Pierrick Bourgeat
Longitudinal analysis has great potential to reveal developmental trajectories and monitor disease progression in medical imaging. This process relies on consistent and robust join…