3 March 2017 Automatic and semi-automatic approaches for arteriolar-to-venular computation in retinal photographs
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Abstract
The Arteriolar-to-Venular Ratio (AVR) is a popular dimensionless measure which allows the assessment of patients’ condition for the early diagnosis of different diseases, including hypertension and diabetic retinopathy. This paper presents two new approaches for AVR computation in retinal photographs which include a sequence of automated processing steps: vessel segmentation, caliber measurement, optic disc segmentation, artery/vein classification, region of interest delineation, and AVR calculation. Both approaches have been tested on the INSPIRE-AVR dataset, and compared with a ground-truth provided by two medical specialists. The obtained results demonstrate the reliability of the fully automatic approach which provides AVR ratios very similar to at least one of the observers. Furthermore, the semi-automatic approach, which includes the manual modification of the artery/vein classification if needed, allows to significantly reduce the error to a level below the human error.
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Ana Maria Mendonça, Ana Maria Mendonça, Beatriz Remeseiro, Beatriz Remeseiro, Behdad Dashtbozorg, Behdad Dashtbozorg, Aurélio Campilho, Aurélio Campilho, } "Automatic and semi-automatic approaches for arteriolar-to-venular computation in retinal photographs", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101341L (3 March 2017); doi: 10.1117/12.2255096; https://doi.org/10.1117/12.2255096
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