Improving retinal artery and vein classification by means of a minimal path approach

Vázquez, S. G.; Cancela, Brais; Barreira, N.; Penedo, Manuel G.; Rodríguez-Blanco, M.; Seijo, Marta Pena; Tuero, Gabriel Coll de; Barceló, María Antònia; Sáez, Marc

doi:10.1007/s00138-012-0442-4

Cited by 74 publications

(63 citation statements)

References 18 publications

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“…SIVA (Vázquez, et al, 2013) developed by the Singapore Eye Research Institute is designed for extraction of the retinal vascular structure and derives quantitative measures from retinal images to describe the retinal vessels' characteristics. IVAN (Grisan & Ruggeri, 2003) is another software tool used for obtaining clinical indexes of AVR, but the time for the analysis of a single image is approximately 20 minutes, too long to allow its use in screening studies or to become a standard in clinical practice (Huang, Zhang, & Huang, 2012).…”

Section: Motivationmentioning

confidence: 99%

QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size – An automated system for quantification of retinal vessels morphology

Fraz

Welikala

Rudnicka

et al. 2015

Expert Systems with Applications

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. . QUARTZ performs well in terms of segmentation accuracy, calibre measurement, optic disc and arteriole/venule recognition. The system provides a rich quantification of retinal vessel morphology, which has potential medical applications in identifying those at high risk, so that prophylactic measure can be initiated before onset of overt disease.

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Section: Motivationmentioning

confidence: 99%

QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size – An automated system for quantification of retinal vessels morphology

Fraz

Welikala

Rudnicka

et al. 2015

Expert Systems with Applications

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“…This application includes a fully automatic method to compute the AVR [16]. This method measures the vessels found in several circumferences centered on the optic disc and classifies them into arteries and veins.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of SIRIUS retinal vessel width measurement in REVIEW dataset

Vázquez

Barreira

Penedo

et al. 2013

Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems

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This paper focuses on evaluating a method for measuring the retinal vessel widths in a recently publicly available database (REVIEW). The algorithm is based on deformable models and it constitutes an essential step in a methodology to compute the AVR automatically. This methodology is part of a web-based framework aimed to integrate diverse techniques in the field of retinal image analysis. The results achieved in the REVIEW database indicate the method is comparable or, in some cases, improves the accuracy of other techniques for measuring the vessel widths.

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“…However, manually identifying artery or vein is a time consuming and laborious work. Therefore, a number of algorithms have been proposed to explore automated A-V classification [11–20]. This requires several steps that include, using precise tools or method to extract the blood vessel map, identify artery and vein, quantify any changes and assess the condition of patient.…”

Section: Introductionmentioning

confidence: 99%

“…This requires several steps that include, using precise tools or method to extract the blood vessel map, identify artery and vein, quantify any changes and assess the condition of patient. A large number of vessel classification algorithms are based on the color and intensity information of artery and vein [13–16, 18–20]. Because of the presence of oxygenated blood, the arteries have lighter color intensity.…”

Section: Introductionmentioning

confidence: 99%

Automated classification and quantitative analysis of arterial and venous vessels in fundus images

Alam

Son

Toslak

et al. 2018

Ophthalmic Technologies XXVIII

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It is known that retinopathies may affect arteries and veins differently. Therefore, reliable differentiation of arteries and veins is essential for computer-aided analysis of fundus images. The purpose of this study is to validate one automated method for robust classification of arteries and veins (A-V) in digital fundus images. We combine optical density ratio (ODR) analysis and blood vessel tracking algorithm to classify arteries and veins. A matched filtering method is used to enhance retinal blood vessels. Bottom hat filtering and global thresholding are used to segment the vessel and skeleton individual blood vessels. The vessel tracking algorithm is used to locate the optic disk and to identify source nodes of blood vessels in optic disk area. Each node can be identified as vein or artery using ODR information. Using the source nodes as starting point, the whole vessel trace is then tracked and classified as vein or artery using vessel curvature and angle information. 50 color fundus images from diabetic retinopathy patients were used to test the algorithm. Sensitivity, specificity, and accuracy metrics were measured to assess the validity of the proposed classification method compared to ground truths created by two independent observers. The algorithm demonstrated 97.52% accuracy in identifying blood vessels as vein or artery. A quantitative analysis upon A-V classification showed that average A-V ratio of width for NPDR subjects with hypertension decreased significantly (43.13%).

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Improving retinal artery and vein classification by means of a minimal path approach

Cited by 74 publications

References 18 publications

QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size – An automated system for quantification of retinal vessels morphology

QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size – An automated system for quantification of retinal vessels morphology

Evaluation of SIRIUS retinal vessel width measurement in REVIEW dataset

Automated classification and quantitative analysis of arterial and venous vessels in fundus images

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