Automated Identification of Referable Retinal Pathology in Teleophthalmology Setting

PURPOSE: This study aims to meet a growing need for a fully automated, learning-based interpretation tool for retinal images obtained remotely (e.g. teleophthalmology) through different imaging modalities that may include imperfect (uninterpretable) images. METHODS: A retrospective study of 1148 opt...

Descripción completa

Detalles Bibliográficos
Autores principales: Gao, Qitong, Amason, Joshua, Cousins, Scott, Pajic, Miroslav, Hadziahmetovic, Majda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161696/
https://www.ncbi.nlm.nih.gov/pubmed/34036304
http://dx.doi.org/10.1167/tvst.10.6.30

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161696/
https://www.ncbi.nlm.nih.gov/pubmed/34036304
http://dx.doi.org/10.1167/tvst.10.6.30

Ejemplares similares