The Arteriolar-to-Venular Ratio (AVR) is a well known index for the diagnosis of diseases such as diabetes, hypertension or cardiovascular pathologies. This paper presents a fully automatic AVR estimation method which uses a graph-based artery/vein classification approach to classify the retinal vessels by a combination of structural information taken from the vasculature graph with intensity features from the original color image. This method was evaluated on the images of the INSPIRE-AVR dataset. The mean error and the correlation coefficient of obtained results with respect to the reference AVR values were identical to the ones obtained by the second observer using a semi-automated system, which demonstrate the potential of the herein proposed solution for clinical application. © 2013 Springer-Verlag.
CITATION STYLE
Dashtbozorg, B., Mendonça, A. M., & Campilho, A. (2013). Automatic estimation of the arteriolar-to-venular ratio in retinal images using a graph-based approach for artery/vein classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7950 LNCS, pp. 530–538). https://doi.org/10.1007/978-3-642-39094-4_60
Mendeley helps you to discover research relevant for your work.