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Automatic Estimation of the Arteriolar-to-Venular Ratio in Retinal Images Using a Graph-Based Approach for Artery/Vein Classification

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Image Analysis and Recognition (ICIAR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7950))

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Abstract

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.

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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: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_60

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  • DOI: https://doi.org/10.1007/978-3-642-39094-4_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39093-7

  • Online ISBN: 978-3-642-39094-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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