ArticleBiomedical optics express2020
Robust non-perfusion area detection in three retinal plexuses using convolutional neural network in OCT angiography.
Article in Biomedical optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
32 citing papers in PubMed, 2 citations in OpenAlex.
- Automated Nonperfusion Quantification in Diabetic Retinopathy on Ultra-Widefield Swept-Source OCT Angiography.Ophthalmology science · 2026Article
- Characterizing Long-Chain 3-Hydroxy-Acyl-CoA Dehydrogenase Deficiency (LCHADD) Chorioretinopathy Using OCT and OCTA.Investigative ophthalmology & visual science · 2025Article
- Wide-field OCTA quantified peripheral nonperfusion areas predict the risk of subclinical neovascularization.Eye (London, England) · 2025Article
- Artificial intelligence-assisted projection-resolved optical coherence tomographic angiography (aiPR-OCTA).Optics express · 2025Article
- Nonperfused Retinal Capillaries-A New Method Developed on OCT and OCTA.Investigative ophthalmology & visual science · 2025Article
- Artificial Intelligence Versus Rules-Based Approach for Segmenting NonPerfusion Area in a DRCR Retina Network Optical Coherence Tomography Angiography Dataset.Investigative ophthalmology & visual science · 2025Article
- Advances in OCT Angiography.Translational vision science & technology · 2025Review
- Multi-Plexus Nonperfusion Area Segmentation in Widefield OCT Angiography Using a Deep Convolutional Neural Network.Translational vision science & technology · 2024Article
- DRAC 2022: A public benchmark for diabetic retinopathy analysis on ultra-wide optical coherence tomography angiography images.Patterns (New York, N.Y.) · 2024Article
- Interpretable Diabetic Retinopathy Diagnosis Based on Biomarker Activation Map.IEEE transactions on bio-medical engineering · 2024Article
- Article
- OCT angiography and its retinal biomarkers [Invited].Biomedical optics express · 2023Review
- Semi-automated algorithm using directional filter for the precise quantification of non-perfusion area on widefield swept-source optical coherence tomography angiograms.Quantitative imaging in medicine and surgery · 2023Article
- Optical Coherence Tomography Angiography in Retinal Vascular Disorders.Diagnostics (Basel, Switzerland) · 2023Review
- Signal attenuation-compensated projection-resolved OCT angiography.Biomedical optics express · 2023Article
- Deep Learning for Diagnosing and Segmenting Choroidal Neovascularization in OCT Angiography in a Large Real-World Data Set.Translational vision science & technology · 2023Article
- Reverse translation of artificial intelligence in glaucoma: Connecting basic science with clinical applications.Frontiers in ophthalmology · 2023Article
- A Deep Learning Network for Classifying Arteries and Veins in Montaged Widefield OCT Angiograms.Ophthalmology science · 2022Article
- Association Between Fluid Volume in Inner Nuclear Layer and Visual Acuity in Diabetic Macular Edema.American journal of ophthalmology · 2022Article
- The intercapillary space spectrum as a marker of diabetic retinopathy severity on optical coherence tomography angiography.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
Non-perfusion area (NPA) is a quantitative biomarker useful for characterizing ischemia in diabetic retinopathy (DR). Projection-resolved optical coherence tomographic angiography (PR-OCTA) allows visualization of retinal capillaries and quantify NPA in individual plexuses. However, poor scan quality can make current NPA detection algorithms unreliable and inaccurate. In this work, we present a robust NPA detection algorithm using convolutional neural network (CNN). By merging information from OCT angiograms and OCT reflectance images, the CNN could exclude signal reduction and motion artifacts and detect the avascular features from local to global with the resolution preserved. Across a wide range of signal strength indices, and on both healthy and DR eyes, the algorithm achieved high accuracy and repeatability.
Identifiers
What OpenQuestion holds
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.