Learning-based approach for the automatic detection of the optic disc in digital retinal fundus photographs

D. W.K. Wong, J. Liu, N. M. Tan, F. Yin, B. H. Lee, T. Y. Wong

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

14 Citations (Scopus)

Abstract

The optic disc is an important feature in the retina. We propose a method for the detection of the optic disc based on a supervised learning scheme. The method employs pixel and local neighbourhood features extracted from the ROI of a digital retinal fundus photograph. A support vector machine based classification mechanism is used to classify each image point as belonging to the cup and retina. The proposed method is evaluated on a sample image set of 68 retinal fundus images. The results show a high correlation (r>0.9) with the ground truth segmentation, with an overlap error of 6.02%, and found to be comparable to the inter-observer variability based on an independent second observer segmentation of the same data set.

Original languageEnglish
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Pages5355-5358
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duration: 31 Aug 20104 Sep 2010

Publication series

Name2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Conference

Conference2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Country/TerritoryArgentina
CityBuenos Aires
Period31/08/104/09/10

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Health Informatics

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