Deep learning for retinal non-perfusion and foveal avascular zone analysis in wide-field OCTA in diabetic retinopathy

Deep learning for retinal non-perfusion and foveal avascular zone analysis in wide-field OCTA in diabetic retinopathy

Abstract We developed an automated framework for segmenting low-quality and non-perfusion areas in widefield OCTA images to obtain two key metrics useful for diabetic retinopathy (DR) monitoring: the retinal non-perfusion index (NPI) and foveal avascular zone (FAZ) area. Using 170 images from 88 pat...

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Bibliographic Details
Main Authors: Hugo Le Boité, Sophie Bonnin, Mathias Gallardo, Mathieu Lamard, Aude Couturier, Gwenolé Quellec
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
OCT-angiography
Retinal non-perfusion
Artificial intelligence
Image segmentation
Diabetic retinopathy
Online Access:https://doi.org/10.1038/s41598-025-15712-3
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https://doi.org/10.1038/s41598-025-15712-3

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