Retinal vessel classification: sorting arteries and veins

D. Relan, T. MacGillivray, L. Ballerini, E. Trucco

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    46 Citations (Scopus)

    Abstract

    For the discovery of biomarkers in the retinal vasculature it is essential to classify vessels into arteries and veins. We automatically classify retinal vessels as arteries or veins based on colour features using a Gaussian Mixture Model, an Expectation-Maximization (GMM-EM) unsupervised classifier, and a quadrant-pairwise approach. Classification is performed on illumination- corrected images. 406 vessels from 35 images were processed resulting in 92% correct classification (when unlabelled vessels are not taken into account) as compared to 87.6%, 90.08%, and 88.28% reported in [12] [14] and [15]. The classifier results were compared against two trained human graders to establish performance parameters to validate the success of classification method. The proposed system results in specificity of (0.8978, 0.9591) and precision (positive predicted value) of (0.9045, 0.9408) as compared to specificity of (0.8920, 0.7918) and precision of (0.8802, 0.8118) for (arteries, veins) respectively as reported in [13]. The classification accuracy was found to be 0.8719 and 0.8547 for veins and arteries, respectively.
    Original languageEnglish
    Title of host publicationProceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    PublisherIEEE
    Pages7396-7399
    Number of pages4
    ISBN (Print)9781457702167
    DOIs
    Publication statusPublished - 2013
    Event35th Annual International Conference of the IEEE EMBS - Osaka, Japan
    Duration: 3 Jul 20137 Jul 2013

    Conference

    Conference35th Annual International Conference of the IEEE EMBS
    CountryJapan
    CityOsaka
    Period3/07/137/07/13

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