• DocumentCode
    3685132
  • Title

    Automatic Gunn and Salus sign quantification in retinal images

  • Author

    Jeffrey Wigdahl;Pedro Guimaraes;Georgios Leontidis;Areti Triantafyllou;Alfredo Ruggeri

  • Author_Institution
    Dept. of Inf. Eng., Univ. of Padova, Padua, Italy
  • fYear
    2015
  • Firstpage
    5251
  • Lastpage
    5254
  • Abstract
    Prolonged hypertension can lead to abnormal changes in the retinal vasculature, including sclerosis and thickening of the arteriole walls. These changes can cause compression (Gunn´s sign) and deflection (Salus´s sign) of the veins at arteriovenous crossings. In retinal images, Gunn´s sign appears as a tapering of the vein at a crossing point, while Salus´s sign presents as an S-shaped curving. This paper presents a method for the automatic quantification of these two signs once a crossover has been detected; combining segmentation, artery vein classification, and morphological feature extraction techniques to calculate vein widths and angles entering and exiting the crossover. The method was tested on a small set of crossings, graded by a set of 3 doctors who were in agreement as having or not having Gunn/Salus sign. Results show separation between the two classes and that we can reliably detect and quantify these sign under the right conditions.
  • Keywords
    "Veins","Image segmentation","Retina","Hypertension","Arteries","Standards","Biomedical imaging"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319576
  • Filename
    7319576