65 citations · 92 across the 7 of their papers we have counts for
9 papers
Geometric-to-Semantic Spherical Transfer Learning for Cortical Sulci Labeling
Saeb Tounsi, Joël Chavas, Pietro Gori +3
Deep learning on cortical surfaces faces a dilemma: capturing the complex topology of over 60 nomenclature-dependent sulci per hemisphere requires high-capacity models, yet the ext…
Representation learning of human cortical folding to reveal long lasting neurodevelopmental signatures
Julien Laval, Robin Guiavarch, Antoine Dufournet +24
The human brain folds in utero, primarily during late gestation. Shortly after birth, cortical folding patterns are established and remain stable thereafter, making them promising…
Self-supervised contrastive learning unveils cortical folding pattern linked to prematurity
Julien Laval, Aymeric Gaudin, Vincent Frouin +5
Brain folding patterns have been reported to carry clinically relevant information. The brain folds mainly during the last trimester of pregnancy, and the process might be durably…
Optimizing contrastive learning for cortical folding pattern detection
Aymeric Gaudin, Louise Guillon, Clara Fischer +4
The human cerebral cortex has many bumps and grooves called gyri and sulci. Even though there is a high inter-individual consistency for the main cortical folds, this is not the ca…
Identification of Rare Cortical Folding Patterns using Unsupervised Deep Learning
Louise Guillon, Joël Chavas, Audrey Bénézit +3
Like fingerprints, cortical folding patterns are unique to each brain even though they follow a general species-specific organization. Some folding patterns have been linked with n…
Conservative Regridding When Grid Cell Edges Are Unknown -- Case of SCRIP
Joël Chavas, Édouard Audit, Laure Coquart +1
Nowadays, climate models rely on couplers. Each complete climate model is broken into different sub-models (oceanic, atmospheric,...), each one working on a different grid. The cou…