ArticleBiomedical optics express2016
Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images.
Article in Biomedical optics express, 2016. 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, 23 citations in OpenAlex.
- Topology-preserving, diameter-specific framework for conjunctival vessel segmentation and tortuosity analysis in diabetes.Scientific reports · 2026Article
- Ultrafast Doppler imaging and ultrasound localization microscopy reveal the complexity of vascular rearrangement in chronic spinal lesion.Scientific reports · 2022Article
- A novel algorithm for cardiovascular screening using conjunctival microcirculatory parameters and blood biomarkers.Scientific reports · 2022Article
- Identifying diabetes from conjunctival images using a novel hierarchical multi-task network.Scientific reports · 2022Article
- Classification of advanced and early stages of diabetic retinopathy from non-diabetic subjects by an ordinary least squares modeling method applied to OCTA images.Biomedical optics express · 2020Article
- Detection of Subclinical Diabetic Retinopathy by Fine Structure Analysis of Retinal Images.Journal of ophthalmology · 2019Article
- Inter-visit variability of conjunctival microvascular hemodynamic measurements in healthy and diabetic retinopathy subjects.Microvascular research · 2018Article
- A clinical correlation of conjunctival microangiopathy with grades of retinopathy in type 2 diabetes mellitus.Medical journal, Armed Forces India · 2017Article
- Assessment of Conjunctival Microvascular Hemodynamics in Stages of Diabetic Microvasculopathy.Scientific reports · 2017Article
- Rubeosis faciei diabeticorum is not associated with oxidative stress and skin autofluorescence.Anais brasileiros de dermatologiaArticle
- Distribution of Different Sized Ocular Surface Vessels in Diabetics and Normal Individuals.Journal of ophthalmic & vision researchArticle
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method's discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring.
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