ArticleBiomedical optics express2020
Reconstruction of high-resolution 6×6-mm OCT angiograms using deep learning.
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 39 papers, 1 of them a synthesis that pooled it.
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
39 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optical coherence tomography angiography in thyroid associated ophthalmopathy: a systematic review.BMC ophthalmology · 2024Pooled it
- Automated Assessment of OCT Angiography Image Quality Using the Artificial Intelligence Ready and Exploratory Atlas for Diabetes Insights Data Set.Ophthalmology science · 2026Article
- Automated Volumetric Segmentation of Microaneurysms on OCT Using Artificial Intelligence.ArXiv · 2026Article
- Cross-Device Field-of-View Scale Differences in Clinical OCT Angiography: Phantom Calibration and Large-Scale Clinical Validation.medRxiv : the preprint server for health sciences · 2026Article
- Automated Nonperfusion Quantification in Diabetic Retinopathy on Ultra-Widefield Swept-Source OCT Angiography.Ophthalmology science · 2026Article
- Retinal Vascular Density and Vessel Diameter in Sturge-Weber Syndrome Assessed by OCT-Angiography.Journal of clinical medicine · 2025Article
- Widefield OCT angiography.Progress in retinal and eye research · 2025Review
- High-resolution multimodal visible light optical coherence tomography and scanning laser ophthalmoscopy forBiomedical optics express · 2025Article
- Three-dimensional C-scan-based generation adversarial network with synthetic input to improve optical coherence tomography angiography.Journal of biomedical optics · 2025Article
- Nonperfused Retinal Capillaries-A New Method Developed on OCT and OCTA.Investigative ophthalmology & visual science · 2025Article
- Advances in OCT Angiography.Translational vision science & technology · 2025Review
- Automated Imaging of Cataract Surgery Using Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2025Article
- AI-based 3D analysis of retinal vasculature associated with retinal diseases using OCT angiography.Biomedical optics express · 2024Article
- Enhanced microvascular imaging through deep learning-driven OCTA reconstruction with squeeze-and-excitation block integration.Biomedical optics express · 2024Article
- Advances in multimodal imaging for diagnosis of pigmented ocular fundus lesions.Canadian journal of ophthalmology. Journal canadien d'ophtalmologie · 2024Review
- Improved microvascular imaging with optical coherence tomography using 3D neural networks and a channel attention mechanism.Scientific reports · 2024Article
- Revealing speckle obscured living human retinal cells with artificial intelligence assisted adaptive optics optical coherence tomography.Communications medicine · 2024Article
- Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine.Journal of personalized medicine · 2023Review
- Optical coherence tomography angiography in diabetic retinopathy.Progress in retinal and eye research · 2023Review
- U-shaped fusion convolutional transformer based workflow for fast optical coherence tomography angiography generation in lips.Biomedical optics express · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Typical optical coherence tomographic angiography (OCTA) acquisition areas on commercial devices are 3×3- or 6×6-mm. Compared to 3×3-mm angiograms with proper sampling density, 6×6-mm angiograms have significantly lower scan quality, with reduced signal-to-noise ratio and worse shadow artifacts due to undersampling. Here, we propose a deep-learning-based high-resolution angiogram reconstruction network (HARNet) to generate enhanced 6×6-mm superficial vascular complex (SVC) angiograms. The network was trained on data from 3×3-mm and 6×6-mm angiograms from the same eyes. The reconstructed 6×6-mm angiograms have significantly lower noise intensity, stronger contrast and better vascular connectivity than the original images. The algorithm did not generate false flow signal at the noise level presented by the original angiograms. The image enhancement produced by our algorithm may improve biomarker measurements and qualitative clinical assessment of 6×6-mm OCTA.
Identifiers
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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.