ArticleBiomedical optics express2020
Deep learning toolbox for automated enhancement, segmentation, and graphing of cortical optical coherence tomography microangiograms.
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 25 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
25 citing papers in PubMed.
- Vascular topological primitives resolve post-ischemic microvascular risk fields and enable early prediction in longitudinal OCTA.Biomedical optics express · 2026Article
- Local Versus Global Binarization Techniques After Frangi Filtering for Optical Coherence Tomography Angiography Based Retinal Vessel Density Assessment in Diabetic Retinopathy.Diagnostics (Basel, Switzerland) · 2026Article
- Longitudinal Assessment of Vascularity in Actinic Keratosis Using Dynamic Optical Coherence Tomography: Practical Considerations and Theoretical Insights.Journal of biophotonics · 2026Article
- The AROMA Dataset for Automatic Detection of Artifact Type and Severity in Retinal Optical Coherence Tomography Angiography.Ophthalmic research · 2026Article
- DERMA-OCTA: A Comprehensive Dataset and Preprocessing Pipeline for Dermatological OCTA Vessel Segmentation.Scientific data · 2025Article
- Machine learning-based method to detect capillary stalling using optical coherence tomography.Biomedical optics express · 2025Article
- Dual acquisition scheme-based optical coherence tomography 3D angiography.Journal of biomedical optics · 2025Article
- Label free, capillary-scale blood flow mapping in vivo reveals that low-intensity focused ultrasound evokes persistent dilation in cortical microvasculature.Communications biology · 2025Article
- Optical coherence tomography (OCT) and OCT angiography: Technological development and applications in brain science.Theranostics · 2025Review
- Three-Dimensional Curved Workflow-Based Optical Coherence Tomography Angiography for Enhancing Atopic Dermatitis Theranostics.Research (Washington, D.C.) · 2025Article
- Bessel beam optical coherence microscopy enables multiscale assessment of cerebrovascular network morphology and function.Light, science & applications · 2024Article
- Towards standardising retinal OCT angiography image analysis with open-source toolbox OCTAVA.Scientific reports · 2024Article
- Neurophotonics: a comprehensive review, current challenges and future trends.Frontiers in neuroscience · 2024Review
- Tail Artifact Removal via Transmittance Effect Subtraction in Optical Coherence Tail Artifact Images.Sensors (Basel, Switzerland) · 2023Article
- Cortical microvascular blood flow velocity mapping by combining dynamic light scattering optical coherence tomography and two-photon microscopy.Journal of biomedical optics · 2023Article
- Near-lifespan longitudinal tracking of brain microvascular morphology, topology, and flow in male mice.Nature communications · 2023Article
- Quantitative optical coherence microscopy of neuron morphology in human entorhinal cortex.Frontiers in neuroscience · 2023Article
- Adaptive dynamic analysis-based optical coherence tomography angiography for blood vessel projection artifact suppression.Biomedical optics express · 2023Article
- Blood vessel tail artifacts suppression in optical coherence tomography angiography.Neurophotonics · 2022Article
- Towards standardizing retinal optical coherence tomography angiography: a review.Light, science & applications · 2022Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Optical coherence tomography angiography (OCTA) is becoming increasingly popular for neuroscientific study, but it remains challenging to objectively quantify angioarchitectural properties from 3D OCTA images. This is mainly due to projection artifacts or "tails" underneath vessels caused by multiple-scattering, as well as the relatively low signal-to-noise ratio compared to fluorescence-based imaging modalities. Here, we propose a set of deep learning approaches based on convolutional neural networks (CNNs) to automated enhancement, segmentation and gap-correction of OCTA images, especially of those obtained from the rodent cortex. Additionally, we present a strategy for skeletonizing the segmented OCTA and extracting the underlying vascular graph, which enables the quantitative assessment of various angioarchitectural properties, including individual vessel lengths and tortuosity. These tools, including the trained CNNs, are made publicly available as a user-friendly toolbox for researchers to input their OCTA images and subsequently receive the underlying vascular network graph with the associated angioarchitectural properties.
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 Socratic graph.