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


Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Wong, DK; Liu, J; Tan, NM; Yin, F; Lee, BH; Wong, TY

Published Date

  • 2010

Published In

Volume / Issue

  • 2010 /

Start / End Page

  • 5355 - 5358

PubMed ID

  • 21096259

Pubmed Central ID

  • 21096259

International Standard Serial Number (ISSN)

  • 1557-170X

Digital Object Identifier (DOI)

  • 10.1109/IEMBS.2010.5626466


  • eng

Conference Location

  • United States