EyeMVP learns OCT-informed CFP representations via cross-modal masked reconstruction on 674k paired triples and reports competitive or superior performance on 15 retinal classification and segmentation tasks.
Eyefound: a multimodal generalist foundation model for ophthalmic imaging
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A structured survey of representation learning methods for retinal OCT image analysis, covering supervised, self-supervised, generative, multimodal, and foundation model approaches along with datasets and open problems.
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EyeMVP: OCT-Informed Fundus Representation Learning via Paired CFP--OCT Pretraining
EyeMVP learns OCT-informed CFP representations via cross-modal masked reconstruction on 674k paired triples and reports competitive or superior performance on 15 retinal classification and segmentation tasks.
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Representation learning from OCT images
A structured survey of representation learning methods for retinal OCT image analysis, covering supervised, self-supervised, generative, multimodal, and foundation model approaches along with datasets and open problems.