Use of multimodal dataset in AI for detecting glaucoma based on fundus photographs assessed with OCT: focus group study on high prevalence of myopia
Journal
BMC medical imaging
Journal Volume
22
Journal Issue
1
Pages
206
Date Issued
2022-11-24
Author(s)
Lim, Wee Shin
Ho, Heng-Yen
Ho, Heng-Chen
Chen, Yan-Wu
Chen, Pao-Ju
Lai, Feipei
Jang, Jyh-Shing Roger
Abstract
Glaucoma is one of the major causes of blindness; it is estimated that over 110 million people will be affected by glaucoma worldwide by 2040. Research on glaucoma detection using deep learning technology has been increasing, but the diagnosis of glaucoma in a large population with high incidence of myopia remains a challenge. This study aimed to provide a decision support system for the automatic detection of glaucoma using fundus images, which can be applied for general screening, especially in areas of high incidence of myopia.
Subjects
Deep learning
Glaucoma
Multimodal learning model
Ophthalmology
SDGs
Publisher
BMC
Type
journal article