Prediction of keratoconus progression using deep learning of anterior segment optical coherence tomography maps

BACKGROUND: To predict keratoconus progression using deep learning of the color-coded maps measured with a swept-source anterior segment optical coherence tomography (As-OCT) device. METHODS: We enrolled 218 keratoconic eyes with and without disease progression. Using deep learning of the 6 color-co...

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Detalles Bibliográficos
Autores principales: Kamiya, Kazutaka, Ayatsuka, Yuji, Kato, Yudai, Shoji, Nobuyuki, Miyai, Takashi, Ishii, Hitoha, Mori, Yosai, Miyata, Kazunori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8422102/
https://www.ncbi.nlm.nih.gov/pubmed/34532424
http://dx.doi.org/10.21037/atm-21-1772

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8422102/
https://www.ncbi.nlm.nih.gov/pubmed/34532424
http://dx.doi.org/10.21037/atm-21-1772

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