Article

Self-supervised contrastive learning improves machine learning discrimination of full thickness macular holes from epiretinal membranes in retinal OCT scans

2023-11-15

Abstract excerpt

There is a growing interest in using computer-assisted models for the detection of macular conditions using optical coherence tomography (OCT) data. As the quantity of clinical scan data of specific conditions is limited, these models are typically developed by fine-tuning a generalized network to classify specific macular conditions of interest. Full thickness macular holes (FTMH) present a condition requiring ti...

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Literature Corpus work: 3a78dd8b-cbc0-5d34-961a-a565a925548f
DOI: 10.1101/2023.11.14.23298513

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