An Artificial Intelligence Enabled System for Retinal Nerve Fiber Layer Thickness Damage Severity Staging

Yousefi, Siamak; Huang, Xiaoqin; Poursoroush, Asma; Majoor, Julek; Lemij, Hans; Vermeer, Koen; Elze, Tobias; Wang, Mengyu; Nouri-Mahdavi, Kouros; Mohammadzadeh, Vahid; Brusini, Paolo; Johnson, Chris

doi:10.1016/j.xops.2023.100389

Ophthalmology Science

2024

DOI: 10.1016/j.xops.2023.100389

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An Artificial Intelligence Enabled System for Retinal Nerve Fiber Layer Thickness Damage Severity Staging

Siamak Yousefi,

Xiaoqin Huang,

Asma Poursoroush

et al.

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Artificial intelligence in glaucoma: opportunities, challenges, and future directions

Huang,

Islam,

Akter

et al. 2023

BioMed Eng OnLine

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Artificial intelligence (AI) has shown excellent diagnostic performance in detecting various complex problems related to many areas of healthcare including ophthalmology. AI diagnostic systems developed from fundus images have become state-of-the-art tools in diagnosing retinal conditions and glaucoma as well as other ocular diseases. However, designing and implementing AI models using large imaging data is challenging. In this study, we review different machine learning (ML) and deep learning (DL) techniques applied to multiple modalities of retinal data, such as fundus images and visual fields for glaucoma detection, progression assessment, staging and so on. We summarize findings and provide several taxonomies to help the reader understand the evolution of conventional and emerging AI models in glaucoma. We discuss opportunities and challenges facing AI application in glaucoma and highlight some key themes from the existing literature that may help to explore future studies. Our goal in this systematic review is to help readers and researchers to understand critical aspects of AI related to glaucoma as well as determine the necessary steps and requirements for the successful development of AI models in glaucoma.

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Artificial intelligence in glaucoma: opportunities, challenges, and future directions

Huang,

Islam,

Akter

et al. 2023

BioMed Eng OnLine

View full text Add to dashboard Cite

show abstract

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An Artificial Intelligence Enabled System for Retinal Nerve Fiber Layer Thickness Damage Severity Staging

Cited by 1 publication

References 35 publications

Artificial intelligence in glaucoma: opportunities, challenges, and future directions

Artificial intelligence in glaucoma: opportunities, challenges, and future directions

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