ArticleThe British journal of ophthalmology2024
Automated expert-level scleral spur detection and quantitative biometric analysis on the ANTERION anterior segment OCT system.
Article in The British journal of ophthalmology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Quantitative Ciliary Body Imaging Using Image-Registered Swept-Source AS-OCT and Ultrasound Biomicroscopy.Translational vision science & technology · 2026Article
- Risk prediction in primary angle closure suspects: current perspectives.Annals of translational medicine · 2026Article
- Comparison of RETFound and a Supervised Convolutional Neural Network for Detection of Referable Glaucoma from Fundus Photographs.Ophthalmology science · 2026Article
- Ocular Biometric Predictors of Corneal Endothelial Contact by Intracameral Implants for Open-Angle Glaucoma and Ocular Hypertension.Translational vision science & technology · 2025Observational
- Acute Angle Closure Incidence in a Large Countywide Safety Net Teleretinal Screening Program.JAMA ophthalmology · 2025Article
- Comparison of Foundation and Supervised Learning-Based Models for Detection of Referable Glaucoma from Fundus Photographs.medRxiv : the preprint server for health sciences · 2025Article
- Machine Learning-Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study.Journal of medical Internet research · 2025Article
- Article
- Prevalence and Risk Factors of Blindness Among Primary Angle Closure Glaucoma Patients in the United States: An IRIS Registry Analysis.American journal of ophthalmology · 2024Article
- Automatic measurement of anterior chamber angle parameters in AS-OCT images using deep learning.Biomedical optics express · 2023Article
- Comparison of Deep Learning and Clinician Performance for Detecting Referable Glaucoma from Fundus Photographs in a Safety Net Population.Ophthalmology scienceArticle
- Artificial intelligence and big data integration in anterior segment imaging for glaucoma.Taiwan journal of ophthalmologyReview
- Applications of deep learning in the analysis of optical coherence tomography images for glaucoma-related diagnostics.Taiwan journal of ophthalmologyReview
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
aimTo perform an independent validation of deep learning (DL) algorithms for automated scleral spur detection and measurement of scleral spur-based biometric parameters in anterior segment optical coherence tomography (AS-OCT) images.
methodsPatients receiving routine eye care underwent AS-OCT imaging using the ANTERION OCT system (Heidelberg Engineering, Heidelberg, Germany). Scleral spur locations were marked by three human graders (reference, expert and novice) and predicted using DL algorithms developed by Heidelberg Engineering that prioritise a false positive rate <4% (FPR4) or true positive rate >95% (TPR95). Performance of human graders and DL algorithms were evaluated based on agreement of scleral spur locations and biometric measurements with the reference grader.
results1308 AS-OCT images were obtained from 117 participants. Median differences in scleral spur locations from reference locations were significantly smaller (p<0.001) for the FPR4 (52.6±48.6 µm) and TPR95 (55.5±50.6 µm) algorithms compared with the expert (61.1±65.7 µm) and novice (79.4±74.9 µm) graders. Intergrader reproducibility of biometric measurements was excellent overall for all four (intraclass correlation coefficient range 0.918-0.997). Intergrader reproducibility of the expert grader (0.567-0.965) and DL algorithms (0.746-0.979) exceeded that of the novice grader (0.146-0.929) for images with narrow angles defined by OCT measurement of angle opening distance 500 µm anterior to the scleral spur (AOD500)<150 µm.
conclusionsDL algorithms on the ANTERION approximate expert-level measurement of scleral spur-based biometric parameters in an independent patient population. These algorithms could enhance clinical utility of AS-OCT imaging, especially for evaluating patients with angle closure and performing intraocular lens calculations.
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