Deep learning algorithms for automatic detection of pterygium using anterior segment photographs from slit-lamp and hand-held cameras

BACKGROUND/AIMS: To evaluate the performances of deep learning (DL) algorithms for detection of presence and extent pterygium, based on colour anterior segment photographs (ASPs) taken from slit-lamp and hand-held cameras. METHODS: Referable pterygium was defined as having extension towards the corn...

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Detalles Bibliográficos
Autores principales: Fang, Xiaoling, Deshmukh, Mihir, Chee, Miao Li, Soh, Zhi-Da, Teo, Zhen Ling, Thakur, Sahil, Goh, Jocelyn Hui Lin, Liu, Yu-Chi, Husain, Rahat, Mehta, Jodhbir, Wong, Tien Yin, Cheng, Ching-Yu, Rim, Tyler Hyungtaek, Tham, Yih-Chung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Clinical Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9685734/
https://www.ncbi.nlm.nih.gov/pubmed/34244208
http://dx.doi.org/10.1136/bjophthalmol-2021-318866

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9685734/
https://www.ncbi.nlm.nih.gov/pubmed/34244208
http://dx.doi.org/10.1136/bjophthalmol-2021-318866

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