4 papers
MongeNet: Efficient Sampler for Geometric Deep Learning
Léo Lebrat, Rodrigo Santa Cruz, Clinton Fookes +1
Recent advances in geometric deep-learning introduce complex computational challenges for evaluating the distance between meshes. From a mesh model, point clouds are necessary alon…
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…
Approximation of curves with piecewise constant or piecewise linear functions
Frédéric de Gournay, Jonas Kahn, Léo Lebrat
In this paper we compute the Hausdorff distance between sets of continuous curves and sets of piecewise constant or linear discretizations. These sets are Sobolev balls given by th…