ArticleBiomedical optics express2019
Robust deep learning method for choroidal vessel segmentation on swept source optical coherence tomography images.
Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Trial
- Region-Specific Retinal and Choroidal Biomarkers Associated with Visual Outcomes After Anti-VEGF Treatment in Center-Involved Diabetic Macular Edema.Clinical ophthalmology (Auckland, N.Z.) · 2026Article
- Optical coherence tomography angiography in neovascular age-related macular degeneration: comprehensive review of advancements and future perspective.Eye (London, England) · 2025Review
- A novel multi-scale and fine-grained network for large choroidal vessels segmentation in OCT.Frontiers in cell and developmental biology · 2025Article
- Choroidalyzer: An Open-Source, End-to-End Pipeline for Choroidal Analysis in Optical Coherence Tomography.Investigative ophthalmology & visual science · 2024Article
- Macular and peripapillary Choroidal Vascularity Index in children with different refractive status.Eye (London, England) · 2024Article
- Choroidal Optical Coherence Tomography Angiography: Noninvasive Choroidal Vessel Analysis via Deep Learning.Health data science · 2024Article
- Optical Coherence Tomography Angiography in Retinal Vascular Disorders.Diagnostics (Basel, Switzerland) · 2023Review
- Deep learning segmentation of the tear fluid reservoir under the sclera lens in optical coherence tomography images.Biomedical optics express · 2023Article
- A Deep Learning-Based Fully Automated Program for Choroidal Structure Analysis Within the Region of Interest in Myopic Children.Translational vision science & technology · 2023Article
- Automated detection and growth tracking of 3D bio-printed organoid clusters using optical coherence tomography with deep convolutional neural networks.Frontiers in bioengineering and biotechnology · 2023Article
- Mitigating the effects of choroidal hyper- and hypo-transmission defects on choroidal vascularity index assessments using optical coherence tomography.Quantitative imaging in medicine and surgery · 2022Article
- Application of Deep Learning Methods for Binarization of the Choroid in Optical Coherence Tomography Images.Translational vision science & technology · 2022Article
- Spatiotemporal absorption fluctuation imaging based on U-Net.Journal of biomedical optics · 2022Article
- Artificial intelligence in OCT angiography.Progress in retinal and eye research · 2021Review
- An end-to-end network for segmenting the vasculature of three retinal capillary plexuses from OCT angiographic volumes.Biomedical optics express · 2021Article
- Framework for quantitative three-dimensional choroidal vasculature analysis using optical coherence tomography.Biomedical optics express · 2021Article
- Design and Pilot data of the high myopia registration study: Shanghai Child and Adolescent Large-scale Eye Study (SCALE-HM).Acta ophthalmologica · 2021Article
- Hybrid deep learning network for vascular segmentation in photoacoustic imaging.Biomedical optics express · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate choroidal vessel segmentation with swept-source optical coherence tomography (SS-OCT) images provide unprecedented quantitative analysis towards the understanding of choroid-related diseases. Motivated by the leading segmentation performance in medical images from the use of deep learning methods, in this study, we proposed the adoption of a deep learning method, RefineNet, to segment the choroidal vessels from SS-OCT images. We quantitatively evaluated the RefineNet on 40 SS-OCT images consisting of ~3,900 manually annotated choroidal vessels regions. We achieved a segmentation agreement (SA) of 0.840 ± 0.035 with clinician 1 (C1) and 0.823 ± 0.027 with clinician 2 (C2). These results were higher than inter-observer variability measure in SA between C1 and C2 of 0.821 ± 0.037. Our results demonstrated that the choroidal vessels from SS-OCT can be automatically segmented using a deep learning method and thus provided a new approach towards an objective and reproducible quantitative analysis of vessel regions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.