Article

Quantitative Characterization of Retinal Features in Translated OCTA

2024-02-27

Abstract excerpt

<h4>Purpose</h4> This study explores the feasibility of using generative machine learning (ML) to translate Optical Coherence Tomography (OCT) images into Optical Coherence Tomography Angiography (OCTA) images, potentially bypassing the need for specialized OCTA hardware. <h4>Methods</h4> The method involved implementing a generative adversarial network framework that includes a 2D vascular segmentation model and...

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Literature Corpus work: 90b5911d-14e2-5762-b514-a442cd8f0450
DOI: 10.1101/2024.02.23.24303275

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