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...
- 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/