3 papers
cs.AI2025
Specialized curricula for training vision-language models in retinal image analysis
Robbie Holland, Thomas R. P. Taylor, Christopher Holmes +13
Clinicians spend a significant amount of time reviewing medical images and transcribing their findings regarding patient diagnosis, referral and treatment in text form. Vision-lang…
cs.CV2024
Metadata-enhanced contrastive learning from retinal optical coherence tomography images
Robbie Holland, Oliver Leingang, Hrvoje BogunoviÄ +9
Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and g…
cs.CV2024
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs
Taha Emre, Arunava Chakravarty, Antoine Rivail +10
Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models. Contrastive methods are a prominent famil…