Keratoconus Detection-based on Dynamic Corneal Deformation Videos Using Deep Learning

OBJECTIVE: To assess the performance of convolutional neural networks (CNNs) for automated detection of keratoconus (KC) in standalone Scheimpflug-based dynamic corneal deformation videos. DESIGN: Retrospective cohort study. PARTICIPANTS: We retrospectively analyzed datasets with records of 734 nonc...

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Detalles Bibliográficos
Autores principales: Abdelmotaal, Hazem, Hazarbassanov, Rossen Mihaylov, Salouti, Ramin, Nowroozzadeh, M. Hossein, Taneri, Suphi, Al-Timemy, Ali H., Lavric, Alexandru, Yousefi, Siamak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10587634/
https://www.ncbi.nlm.nih.gov/pubmed/37868800
http://dx.doi.org/10.1016/j.xops.2023.100380

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10587634/
https://www.ncbi.nlm.nih.gov/pubmed/37868800
http://dx.doi.org/10.1016/j.xops.2023.100380

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