Assessing Fuchs Corneal Endothelial Dystrophy Using Artificial Intelligence-Derived Morphometric Parameters From Specular Microscopy Images

Purpose: The aim of this study was to evaluate the efficacy of artificial intelligence–derived morphometric parameters in characterizing Fuchs corneal endothelial dystrophy (FECD) from specular microscopy images. Methods: This cross-sectional study recruited patients diagnosed with FECD, who underwe...

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Autores:
Prada, Angelica M.
Quintero, Fernando
Mendoza, Kevin
Galvis, Virgilio
Tello, Alejandro
Romero, Lenny A
Marrugo, Andres G.
Tipo de recurso:
Fecha de publicación:
2024
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12706
Acceso en línea:
https://hdl.handle.net/20.500.12585/12706
Palabra clave:
Fuchs dystrophy
Specular microscopy
Endothelial cell density
Artificial intelligence,
Deep learning
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/