A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collect...

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Detalles Bibliográficos
Autores principales: Al-Timemy, Ali H., Alzubaidi, Laith, Mosa, Zahraa M., Abdelmotaal, Hazem, Ghaeb, Nebras H., Lavric, Alexandru, Hazarbassanov, Rossen M., Takahashi, Hidenori, Gu, Yuantong, Yousefi, Siamak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217517/
https://www.ncbi.nlm.nih.gov/pubmed/37238174
http://dx.doi.org/10.3390/diagnostics13101689

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217517/
https://www.ncbi.nlm.nih.gov/pubmed/37238174
http://dx.doi.org/10.3390/diagnostics13101689

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