ArticleThe British journal of ophthalmology2023
Reproducibility of deep learning based scleral spur localisation and anterior chamber angle measurements from anterior segment optical coherence tomography images.
Article in The British journal of ophthalmology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Quantitative Ciliary Body Imaging Using Image-Registered Swept-Source AS-OCT and Ultrasound Biomicroscopy.Translational vision science & technology · 2026Article
- A deep learning-based classification method for subclinical zonular laxity in AS-OCT images.Frontiers in cell and developmental biology · 2026Article
- Assessment of iris pigment epithelium depolarization and associated factors using polarization-sensitive anterior segment optical coherence tomography.International ophthalmology · 2025Article
- Deep learning-based anterior segment identification and parameter assessment of primary angle closure disease in ultrasound biomicroscopy images.BMJ open ophthalmology · 2025Article
- Diagnostic criteria of anterior segment swept-source optical coherence tomography to detect gonioscopic angle closure.The British journal of ophthalmology · 2024Article
- Agreement and Reproducibility of Anterior Chamber Angle Measurements between CASIA2 Built-In Software and Human Graders.Journal of clinical medicine · 2023Article
- Machine learning-couched treatment algorithms tailored to individualized profile of patients with primary anterior chamber angle closure predisposed to the glaucomatous optic neuropathy.The EPMA journal · 2023Article
- Artificial Intelligence for Anterior Segment Diseases: A Review of Potential Developments and Clinical Applications.Ophthalmology and therapy · 2023Review
- Application of artificial intelligence in glaucoma care: An updated review.Taiwan journal of ophthalmologyReview
- Artificial intelligence and big data integration in anterior segment imaging for glaucoma.Taiwan journal of ophthalmologyReview
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13 authors.
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Abstract
aimsTo apply a deep learning model for automatic localisation of the scleral spur (SS) in anterior segment optical coherence tomography (AS-OCT) images and compare the reproducibility of anterior chamber angle (ACA) width between deep learning located SS (DLLSS) and manually plotted SS (MPSS).
methodsIn this multicentre, cross-sectional study, a test dataset comprising 5166 AS-OCT images from 287 eyes (116 healthy eyes with open angles and 171 eyes with primary angle-closure disease (PACD)) of 287 subjects were recruited from four ophthalmology clinics. Each eye was imaged twice by a swept-source AS-OCT (CASIA2, Tomey, Nagoya, Japan) in the same visit and one eye of each patient was randomly selected for measurements of ACA. The agreement between DLLSS and MPSS was assessed using the Euclidean distance (ED). The angle opening distance (AOD) of 750 µm (AOD750) and trabecular-iris space area (TISA) of 750 µm (TISA750) were calculated using the CASIA2 embedded software. The repeatability of ACA width was measured.
resultsThe mean age was 60.8±12.3 years (range: 30-85 years) for the normal group and 63.4±10.6 years (range: 40-91 years) for the PACD group. The mean difference in ED for SS localisation between DLLSS and MPSS was 66.50±20.54 µm and 84.78±28.33 µm for the normal group and the PACD group, respectively. The span of 95% limits of agreement between DLLSS and MPSS was 0.064 mm for AOD750 and 0.034 mm
conclusionDLLSS achieved comparable repeatability compared with MPSS for measurement of ACA.
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