Generalizability of deep neural networks for vertical cup-to-disc ratio estimation in ultra-widefield and amartphone-based fundus images

Generalizability of deep neural networks for vertical cup-to-disc ratio estimation in ultra-widefield and amartphone-based fundus images

Purpose: To develop and validate a deep learning system (DLS) for estimation of vertical cup-to-disc ratio (vCDR) in ultra-widefield (UWF) and smartphone-based fundus images. Methods: A DLS consisting of two sequential convolutional neural networks (CNNs) to delineate optic disc (OD) and optic cup (...

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書目詳細資料
Main Authors:	Yap, Boon Peng, Li, Kelvin Zhenghao, Toh, En Qi, Low, Kok Yao, Rani, Sumaya Khan, Goh, Eunice Jin Hui, Hui, Vivien Yip Cherng, Ng, Beng Koon, Lim, Tock Han
其他作者:	School of Electrical and Electronic Engineering
格式:	Article
語言:	English
出版:	2024
主題:	Engineering Deep learning Optic disc
在線閱讀:	https://hdl.handle.net/10356/179838
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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