Semantic segmentation of gonio-photographs via adaptive ROI localisation and uncertainty estimation

OBJECTIVE: To develop and test a deep learning (DL) model for semantic segmentation of anatomical layers of the anterior chamber angle (ACA) in digital gonio-photographs. METHODS AND ANALYSIS: We used a pilot dataset of 274 ACA sector images, annotated by expert ophthalmologists to delineate five an...

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Detalles Bibliográficos
Autores principales: Peroni, Andrea, Paviotti, Anna, Campigotto, Mauro, Abegão Pinto, Luis, Cutolo, Carlo Alberto, Gong, Jacintha, Patel, Sirjhun, Cobb, Caroline, Gillan, Stewart, Tatham, Andrew, Trucco, Emanuele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Glaucoma
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627415/
https://www.ncbi.nlm.nih.gov/pubmed/34901467
http://dx.doi.org/10.1136/bmjophth-2021-000898

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627415/
https://www.ncbi.nlm.nih.gov/pubmed/34901467
http://dx.doi.org/10.1136/bmjophth-2021-000898

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