Keratoconus detection of changes using deep learning of colour-coded maps

OBJECTIVE: To evaluate the accuracy of convolutional neural networks technique (CNN) in detecting keratoconus using colour-coded corneal maps obtained by a Scheimpflug camera. DESIGN: Multicentre retrospective study. METHODS AND ANALYSIS: We included the images of keratoconic and healthy volunteers’...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Xu, Zhao, Jiaxin, Iselin, Katja C, Borroni, Davide, Romano, Davide, Gokul, Akilesh, McGhee, Charles N J, Zhao, Yitian, Sedaghat, Mohammad-Reza, Momeni-Moghaddam, Hamed, Ziaei, Mohammed, Kaye, Stephen, Romano, Vito, Zheng, Yalin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Cornea and Ocular Surface
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278890/
https://www.ncbi.nlm.nih.gov/pubmed/34337155
http://dx.doi.org/10.1136/bmjophth-2021-000824

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278890/
https://www.ncbi.nlm.nih.gov/pubmed/34337155
http://dx.doi.org/10.1136/bmjophth-2021-000824

Ejemplares similares