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arXiv · 2405.08397

Self-supervised contrastive learning unveils cortical folding pattern linked to prematurity

Julien Laval·Aymeric Gaudin·Vincent Frouin·Jessica Dubois·Andrea Gondova·Jean-François Mangin·Joël Chavas·Denis Rivière
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Abstract

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 disturbed by preterm birth. Yet little is known about preterm-specific patterns. In this work, we train a self-supervised model (SimCLR) on the UKBioBank cohort (21070 adults) to represent the right superior temporal sulcus (STS) region and apply it to sulci images of 374 babies from the dHCP database, containing preterms and full-terms, and acquired at 40 weeks post-menstrual age. We find a lower variability in the preterm embeddings, supported by the identification of a knob pattern, missing in the extremely preterm population.

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Julien Laval, Aymeric Gaudin, Vincent Frouin, Jessica Dubois, Andrea Gondova, Jean-François Mangin, Joël Chavas, Denis Rivière. 2024-05-14. Self-supervised contrastive learning unveils cortical folding pattern linked to prematurity. https://arxiv.org/abs/2405.08397

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