ArticleBiomedical optics express2021
Framework for quantitative three-dimensional choroidal vasculature analysis using optical coherence tomography.
Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Comparison of Three-Dimensional Choroidal Contour in Patients With Neovascular Age-Related Macular Degeneration and Their Fellow Eyes.Translational vision science & technology · 2025Article
- Interocular differences in choroidal thickness and circulation in anisomyopic adults and their association with myopia severity.Frontiers in medicine · 2025Article
- Depth-resolved visualization and automated quantification of hyperreflective foci on OCT scans using optical attenuation coefficients.Biomedical optics express · 2022Article
- Application of Deep Learning Methods for Binarization of the Choroid in Optical Coherence Tomography Images.Translational vision science & technology · 2022Article
- Article
- Value of Combining Optical Coherence Tomography with Fundus Photography in Screening Retinopathy in Patients with High Myopia.Journal of healthcare engineering · 2022Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Choroidal vasculature plays an important role in the pathogenesis of retinal diseases, such as myopic maculopathy, age-related macular degeneration, diabetic retinopathy, central serous chorioretinopathy, and ocular inflammatory diseases. Current optical coherence tomography (OCT) technology provides three-dimensional visualization of the choroidal angioarchitecture; however, quantitative measures remain challenging. Here, we propose and validate a framework to segment and quantify the choroidal vasculature from a prototype swept-source OCT (PLEX Elite 9000, Carl Zeiss Meditec, USA) using a 3×3 mm scan protocol centered on the macula. Enface images referenced from the retinal pigment epithelium were reconstructed from the volumetric data. The boundaries of the choroidal volume were automatically identified by tracking the choroidal vessel feature structure over the depth, and a selective sliding window was applied for segmenting the vessels adaptively from attenuation-corrected enface images. We achieved a segmentation accuracy of 96% ± 1% as compared with manual annotation, and a dice coefficient of 0.83 ± 0.04 for repeatability. Using this framework on both control (0.00 D to -2.00 D) and highly myopic (-8.00 D to -11.00 D) eyes, we report a decrease in choroidal vessel volume (p<0.001) in eyes with high myopia.
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Registered trials
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