Abstract
The Arteriolar-to-Venular Ratio (AVR) is an index used for the early diagnosis of diseases such as diabetes, hypertension or cardiovascular pathologies. This paper presents three automatic approaches for the estimation of the AVR in retinal images that result from the combination of different methodologies in some of the processing phases used for AVR estimation. Each one of these methods includes vessel segmentation, vessel caliber estimation, optic disc detection or segmentation, region of interest determination, vessel classification into arteries and veins and finally AVR calculation. The values produced by the proposed methods on 40 images of the INSPIRE-AVR dataset were compared with a ground-truth obtained by two medical experts using a semi-automated system. The results showed that the measured AVRs are not statistically different from the reference, with mean errors similar to those achieved by the two experts, thus demonstrating the reliability of the herein proposed approach for AVR estimation.
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This work was financed by the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project UID/EEA/50014/2013 and research grant SFRH/BD/73376/2010.
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Dashtbozorg, B., Mendonça, A.M., Campilho, A. (2015). Assessment of Retinal Vascular Changes Through Arteriolar-to-Venular Ratio Calculation. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2015. Lecture Notes in Computer Science(), vol 9164. Springer, Cham. https://doi.org/10.1007/978-3-319-20801-5_36
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