ArticleOphthalmology science2021
A Deep Learning Architecture for Vascular Area Measurement in Fundus Images.
Article in Ophthalmology science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
- Retinal Vessel Traits and the Risk of Stroke: The Canadian Longitudinal Study on Aging.Ophthalmology science · 2026Article
- A deep learning-based pachychoroid index based on choroidal image patterns of central serous chorioretinopathy using enhanced-depth-imaging optical coherence tomography.Japanese journal of ophthalmology · 2026Observational
- Inter-Relationships Between the Deep Learning-Based Pachychoroid Index and Clinical Features Associated with Neovascular Age-Related Macular Degeneration.Journal of clinical medicine · 2025Article
- Artificial intelligence in retinal image analysis for hypertensive retinopathy diagnosis: a comprehensive review and perspective.Visual computing for industry, biomedicine, and art · 2025Review
- Factors Associated With Retinal Vessel Traits in the Canadian Longitudinal Study on Aging.Investigative ophthalmology & visual science · 2025Article
- Retinal Arteriovenous Information Improves the Prediction Accuracy of Deep Learning-Based baPWV Index From Color Fundus Photographs.Investigative ophthalmology & visual science · 2025Article
- Grad-CAM-Based Investigation into Acute-Stage Fluorescein Angiography Images to Predict Long-Term Visual Prognosis of Branch Retinal Vein Occlusion.Journal of clinical medicine · 2024Article
- Development of an Automated Morphometric Approach to Assess Vascular Outcomes following Exposure to Environmental Chemicals in Zebrafish.Environmental health perspectives · 2024Article
- Deep learning-based fundus image analysis for cardiovascular disease: a review.Therapeutic advances in chronic disease · 2023Review
- An Automatic Detection and Classification System of Five Stages for Hypertensive Retinopathy Using Semantic and Instance Segmentation in DenseNet Architecture.Sensors (Basel, Switzerland) · 2021Article
- Why Ophthalmology Science?Ophthalmology science · 2021Article
- Sex Differences in Age-Related Changes in Retinal Arteriovenous Area Based on Deep Learning Segmentation Model.Ophthalmology scienceArticle
- Mean Arteriolar Diameter Measured from Wide-Field Swept-Source OCT Angiography: A Highly Sensitive Indicator for Mean Arterial Pressure.Ophthalmology scienceArticle
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To develop a novel evaluation system for retinal vessel alterations caused by hypertension using a deep learning algorithm. Design: Retrospective study. Participants: Fundus photographs (n = 10 571) of health-check participants (n = 5598). Methods: The participants were analyzed using a fully automatic architecture assisted by a deep learning system, and the total area of retinal arterioles and venules was assessed separately. The retinal vessels were extracted automatically from each photograph and categorized as arterioles or venules. Subsequently, the total arteriolar area (AA) and total venular area (VA) were measured. The correlations among AA, VA, age, systolic blood pressure (SBP), and diastolic blood pressure were analyzed. Six ophthalmologists manually evaluated the arteriovenous ratio (AVR) in fundus images (n = 102), and the correlation between the SBP and AVR was evaluated manually. Main Outcome Measures: Total arteriolar area and VA. Results: The deep learning algorithm demonstrated favorable properties of vessel segmentation and arteriovenous classification, comparable with pre-existing techniques. Using the algorithm, a significant positive correlation was found between AA and VA. Both AA and VA demonstrated negative correlations with age and blood pressure. Furthermore, the SBP showed a higher negative correlation with AA measured by the algorithm than with AVR. Conclusions: The current data demonstrated that the retinal vascular area measured with the deep learning system could be a novel index of hypertension-related vascular changes.
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