Automatic graph-based method for classification of retinal vascular bifurcations and crossovers

Z. Ghanaei, H. Pourreza, T. Banaee

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

Abstract

Implementing an automatic algorithm for classification of retinal vessel landmarks as bifurcation and crossovers will help the experts to analyze retinal images and detect the abnormalities of vascular topology in less time. It also can be used as the initial step of an automatic vessel classification system which is worthwhile in automatic screening programs. In this paper, we proposed a graph based method for automatic classification of vessel landmarks which consist of three steps: generating vasculature graph from centerline image, modifying the extracted graph to reduce the errors and finally classifying vessel landmarks as bifurcations and crossovers. We evaluated the proposed method by comparing the results with manually labeled images from DRIVE dataset. The average accuracy for detection of bifurcations and crossovers are 86.5% and 58.7% respectively.

Original languageEnglish (US)
Title of host publication2016 6th International Conference on Computer and Knowledge Engineering, ICCKE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages229-234
Number of pages6
ISBN (Electronic)9781509035861
DOIs
StatePublished - Dec 29 2016
Externally publishedYes
Event6th International Conference on Computer and Knowledge Engineering, ICCKE 2016 - Mashhad, Iran, Islamic Republic of
Duration: Oct 20 2016 → …

Publication series

Name2016 6th International Conference on Computer and Knowledge Engineering, ICCKE 2016

Conference

Conference6th International Conference on Computer and Knowledge Engineering, ICCKE 2016
CountryIran, Islamic Republic of
CityMashhad
Period10/20/16 → …

Keywords

  • Automatic Classification
  • Bifurcation
  • Crossover
  • Graph
  • Retinal Vessel Landmarks

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems

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