RetinaCAD, a system for the assessment of retinal vascular changes

Dashtbozorg, Behdad; Mendonça, Ana Maria; Penas, Susana; Campilho, Aurélio

doi:10.1109/embc.2014.6945076

Cited by 14 publications

(14 citation statements)

References 11 publications

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“…The advances of computer programs developed for medical imaging have facilitated several computerized measurements on captured retinal images for discovering the relationship between retinal changes and clinical diseases. 11,12 There are increasing data on the retinal changes and some diseases, including those affecting the brain. Several studies have revealed a relationship between retinal vascular changes and the incidence of dementia.…”

Section: Introductionmentioning

confidence: 99%

Association between Retinal Vascular Geometric Changes and Cognitive Impairment: A Systematic Review and Meta-Analysis

Wang

Chen

et al. 2020

J Clin Neurol

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Background and Purpose Previous studies have explored the association between retinal vascular changes and cognitive impairment. The retinal vasculature shares some characteristics with the cerebral vasculature, and quantitative changes in it could indicate cognitive impairment. Hence, a comprehensive meta-analysis was performed to clarify the potential relationship between retinal vascular geometric changes and cognitive impairment. Methods Relevant databases were scrupulously and systematically searched for retinal vascular geometric changes including caliber, tortuosity, and fractal dimension (FD), and for cognitive impairment. The Newcastle-Ottawa Scale was used to evaluate the methodological quality of included studies. RevMan was used to perform the meta-analysis and detect publication bias. Sensitivity analyses were also performed. Results Five studies that involved 2,343 subjects were finally included in the meta-analysis. The results showed that there was no significant association between central retinal artery equivalents (Z=1.17) or central retinal venular equivalents (Z=1.74) and cognitive impairment (both p>0.05). Similarly, no significant difference was detected in retinal arteriolar tortuosity (Z=0.91) and venular tortuosity (Z=1.31) (both p>0.05). However, the retinal arteriolar FD (mean difference:-0.03, 95% CI:-0.05,-0.01) and venular FD (mean difference:-0.03, 95% CI:-0.05,-0.02) were associated with cognitive impairment. Conclusions A smaller retinal microvascular FD might be associated with cognitive impairment. Further large-sample and well-controlled original studies are required to confirm the present findings.

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Section: Introductionmentioning

confidence: 99%

Association between Retinal Vascular Geometric Changes and Cognitive Impairment: A Systematic Review and Meta-Analysis

Wang

Chen

et al. 2020

J Clin Neurol

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“…INSPIRE-AVR data set (referred as INSPIRE) is a public data set provided by Niemeijer et al (2011). It contains 40 OD-centred images at resolution 2392 Â 2048, where the vessel centrelines and the vessel types are labelled by Dashtbozorg et al (2014a).…”

Section: Inspire-avr Data Setmentioning

confidence: 99%

“…Computer-aided diagnosis (CAD) systems (Doi 2007;Van Ginneken et al 2001;Giger 2000;Tan et al 2013, Tan et al 2012Kozegar et al 2017;Tan et al 2015;Somasundaram and Alli 2017;Niemeijer et al 2010;Welikala et al 2014;Sinthanayothin et al 2002;Tavakoli et al 2013;Antal and Hajdu 2014;Pourreza-Shahri et al 2014) have been developed for different diagnosis purposes in medical imaging field. Due to the importance of the retinal vasculature, different computerassisted platforms like the Integrative Vessel Analysis (IVAN) (Niemeijer et al 2011), the Singapore I Vessel Assessment (Ng et al 2014) and the RetinaCAD (Dashtbozorg et al 2014a) were developed for the assessment of vascular changes. These softwares apply different retinal vessel analysis methods to identify the status of diabetes.…”

Section: Introductionmentioning

confidence: 99%

A fully automated pipeline of extracting biomarkers to quantify vascular changes in retina-related diseases

Zhang

Dashtbozorg

Huang

et al. 2018

Computer Methods in Biomechanics and Biomedical Engineering: Im

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This paper presents an automated system for extracting retinal vascular biomarkers for early detection of diabetes. The proposed retinal vessel enhancement, segmentation, optic disc (OD) and fovea detection algorithms provide fundamental tools for extracting the vascular network within the predefined region of interest. Based on that, the artery/vein classification, vessel width, tortuosity and fractal dimension measurement tools are used to assess a large number of quantitative vascular biomarkers. We evaluate our pipeline module by module against human annotations. The results indicate that our automated system is robust to the localisation of OD and fovea, segmentation of vessels and classification of arteries/veins. The proposed pipeline helps to increase the effectiveness of the biomarkers extraction and analysis for the early diabetes, and therefore, has the large potential of being further incorporated into a computer-aided diagnosis system.

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“…In addition, previous works on retinal fractal dimension [4] and vascular tortuosity [5] implied that traditional retinal biomarkers might reveal more information for disease progression if they were measured separately on arteries and veins. Therefore, A/V classification is a necessary step for the measurement of retinal vascular biomarkers, such as central artery equivalent and central vein equivalent and artery-to-vein diameter ratio (AVR) [6,7]. However, the analysis of separated trees of artery and vein has received limited attention, and it is still open for investigation.…”

Section: Introductionmentioning

confidence: 99%

Artery/vein classification using reflection features in retina fundus images

Huang

Dashtbozorg

Romeny

2017

Machine Vision and Applications

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Automatic artery/vein (A/V) classification is one of the important topics in retinal image analysis. It allows the researchers to investigate the association between biomarkers and disease progression on a huge amount of data for arteries and veins separately. Recent proposed methods, which employ contextual information of vessels to achieve better A/V classification accuracy, still rely on the performance of pixel-wise classification, which has received limited attention in recent years. In this paper, we show that these classification methods can be markedly improved. We propose a new normalization technique for extracting four new features which are associated with the lightness reflection of vessels. The accuracy of a linear discriminate analysis classifier is used to validate these features. Accuracy rates of 85.1, 86.9 and 90.6% were obtained on three datasets using only local information. Based on the introduced features, the advanced graph-based methods will achieve a better performance on A/V classification.

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RetinaCAD, a system for the assessment of retinal vascular changes

Cited by 14 publications

References 11 publications

Association between Retinal Vascular Geometric Changes and Cognitive Impairment: A Systematic Review and Meta-Analysis

Association between Retinal Vascular Geometric Changes and Cognitive Impairment: A Systematic Review and Meta-Analysis

A fully automated pipeline of extracting biomarkers to quantify vascular changes in retina-related diseases

Artery/vein classification using reflection features in retina fundus images

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