1 citations · 1 across the 3 of their papers we have counts for
3 papers
Are Traditional Deep Learning Model Approaches as Effective as a Retinal-Specific Foundation Model for Ocular and Systemic Disease Detection?
Samantha Min Er Yew, Xiaofeng Lei, Jocelyn Hui Lin Goh +26
Background: RETFound, a self-supervised, retina-specific foundation model (FM), showed potential in downstream applications. However, its comparative performance with traditional d…
Enhancing Contrastive Learning for Retinal Imaging via Adjusted Augmentation Scales
Zijie Cheng, Boxuan Li, André Altmann +2
Contrastive learning, a prominent approach within self-supervised learning, has demonstrated significant effectiveness in developing generalizable models for various applications i…
Block Expanded DINORET: Adapting Natural Domain Foundation Models for Retinal Imaging Without Catastrophic Forgetting
Jay Zoellin, Colin Merk, Mischa Buob +12
Integrating deep learning into medical imaging is poised to greatly advance diagnostic methods but it faces challenges with generalizability. Foundation models, based on self-super…