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Representation Transfer of Foundation Models for Ultra-Widefield Retinal Imaging
Despite the widespread adoption of foundation models as feature extractors for medical imaging, relatively little is understood about how different pretraining strategies influence the transferability of learned representations to weakly supervised ophthalmic imaging tasks. We investigate this quest
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