ReviewDiagnostics (Basel, Switzerland)2023
Deep Learning in Optical Coherence Tomography Angiography: Current Progress, Challenges, and Future Directions.
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 41 citations in OpenAlex.
- Advances in photoacoustic imaging reconstruction and quantitative analysis for biomedical applications.Visual computing for industry, biomedicine, and art · 2026Review
- Artificial intelligence in refractive surgery: progress, challenges, and future directions.Frontiers in cell and developmental biology · 2026Review
- Design and application of a web-based intelligent ophthalmic image analysis teaching platform.Frontiers in medicine · 2026Article
- Artificial Intelligence Applications in Ophthalmology.JMA journal · 2025Review
- Article
- Artificial intelligence for posterior capsule opacification.Frontiers in medicine · 2025Review
- Article
- Dense Convolutional Neural Network-Based Deep Learning Pipeline for Pre-Identification of Circular Leaf Spot Disease ofSensors (Basel, Switzerland) · 2024Article
- High Prevalence of Artifacts in Optical Coherence Tomography With Adequate Signal Strength.Translational vision science & technology · 2024Article
- Quantitative Characterization of Retinal Features in Translated OCTA.medRxiv : the preprint server for health sciences · 2024Article
- Computational Retinal Microvascular Biomarkers from an OCTA Image in Clinical Investigation.Biomedicines · 2024Article
- Improving the radiological diagnosis of hepatic artery thrombosis after liver transplantation: Current approaches and future challenges.World journal of transplantation · 2024Article
- Correlations between Retinal Microvascular Parameters and Clinical Parameters in Young Patients with Type 1 Diabetes Mellitus: An Optical Coherence Tomography Angiography Study.Diagnostics (Basel, Switzerland) · 2024Article
- Inter-rater reliability in labeling quality and pathological features of retinal OCT scans: A customized annotation software approach.PloS one · 2024Article
- Quantitative characterization of retinal features in translated OCTA.Experimental biology and medicine (Maywood, N.J.) · 2024Article
- Addressing inter-device variations in optical coherence tomography angiography: will image-to-image translation systems help?International journal of retina and vitreous · 2023Article
- Optical Coherence Tomography Angiography of the Intestine: How to Prevent Motion Artifacts in Open and Laparoscopic Surgery?Life (Basel, Switzerland) · 2023Article
- Optical coherence tomography angiography for macular microvessels in ischemic branch retinal vein occlusion treated with conbercept: predictive factors for the prognosis.International journal of ophthalmology · 2023Article
- Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images.Frontiers in cell and developmental biology · 2023Review
- Evaluation of Structural Retinal Layer Alterations in Retinitis Pigmentosa.Romanian journal of ophthalmologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
Optical coherence tomography angiography (OCT-A) provides depth-resolved visualization of the retinal microvasculature without intravenous dye injection. It facilitates investigations of various retinal vascular diseases and glaucoma by assessment of qualitative and quantitative microvascular changes in the different retinal layers and radial peripapillary layer non-invasively, individually, and efficiently. Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks, has been applied in OCT-A image analysis in recent years and achieved good performance for different tasks, such as image quality control, segmentation, and classification. DL technologies have further facilitated the potential implementation of OCT-A in eye clinics in an automated and efficient manner and enhanced its clinical values for detecting and evaluating various vascular retinopathies. Nevertheless, the deployment of this combination in real-world clinics is still in the "proof-of-concept" stage due to several limitations, such as small training sample size, lack of standardized data preprocessing, insufficient testing in external datasets, and absence of standardized results interpretation. In this review, we introduce the existing applications of DL in OCT-A, summarize the potential challenges of the clinical deployment, and discuss future research directions.
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What Socratic 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 Socratic graph.