ArticleExperimental biology and medicine (Maywood, N.J.)2021
A novel multiple subdivision-based algorithm for quantitative assessment of retinal vascular tortuosity.
Article in Experimental biology and medicine (Maywood, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- A Method for Peripapillary Retinal Vessel Tortuosity Measurement and Its Clinical Correspondence.Translational vision science & technology · 2025Article
- Standardizing image acquisition and processing methods: a critical need for the accurate assessment of retinal blood vessel tortuosity.Biomedical optics express · 2025Article
- Segmentation and multiparametric evaluation of corneal whorl-like nerves for in vivo confocal microscopy images in dry eye disease.BMJ open ophthalmology · 2024Article
- Combining functional and morphological retinal vascular characteristics achieves high-precision diagnosis of mild non-proliferative diabetic retinopathy.Journal of translational medicine · 2024Article
- Analysis and comparison of retinal vascular parameters under different glucose metabolic status based on deep learning.International journal of ophthalmology · 2024Article
- Oxygen-saturation-related functional parameter as a biomarker for diabetes mellitus-extraction method and clinical validation.Frontiers in cell and developmental biology · 2023Article
- Retinal Vessel Automatic Segmentation Using SegNet.Computational and mathematical methods in medicine · 2022Article
- Emerging imaging developments in experimental vision sciences and ophthalmology.Experimental biology and medicine (Maywood, N.J.) · 2021Article
- Macular Vascular Geometry Changes With Sex and Age in Healthy Subjects: A Fundus Photography Study.Frontiers in medicine · 2021Article
- Geometrical Features of Subbasal Corneal Whorl-like Nerve Patterns in Dry Eye Disease: An In Vivo Confocal Microscopy Study.Ophthalmology scienceArticle
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8 authors.
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Abstract
Vascular tortuosity as an indicator of retinal vascular morphological changes can be quantitatively analyzed and used as a biomarker for the early diagnosis of relevant disease such as diabetes. While various methods have been proposed to evaluate retinal vascular tortuosity, the main obstacle limiting their clinical application is the poor consistency compared with the experts' evaluation. In this research, we proposed to apply a multiple subdivision-based algorithm for the vessel segment vascular tortuosity analysis combining with a learning curve function of vessel curvature inflection point number, emphasizing the human assessment nature focusing not only global but also on local vascular features. Our algorithm achieved high correlation coefficients of 0.931 for arteries and 0.925 for veins compared with clinical grading of extracted retinal vessels. For the prognostic performance against experts' prediction in retinal fundus images from diabetic patients, the area under the receiver operating characteristic curve reached 0.968, indicating a good consistency with experts' predication in full retinal vascular network evaluation.
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