Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression

PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progression. METHODS: Wide-angle SS-OCT, OCT circumpapill...

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Detalles Bibliográficos
Autores principales: Christopher, Mark, Belghith, Akram, Weinreb, Robert N., Bowd, Christopher, Goldbaum, Michael H., Saunders, Luke J., Medeiros, Felipe A., Zangwill, Linda M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2018
Materias:
Glaucoma
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983908/
https://www.ncbi.nlm.nih.gov/pubmed/29860461
http://dx.doi.org/10.1167/iovs.17-23387

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983908/
https://www.ncbi.nlm.nih.gov/pubmed/29860461
http://dx.doi.org/10.1167/iovs.17-23387

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