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

Journal Article (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

  • Annu Int Conf Ieee Eng Med Biol Soc

Volume / Issue

  • 2010 /

Start / End Page

  • 5355 - 5358

PubMed ID

  • 21096259

International Standard Serial Number (ISSN)

  • 2375-7477

Digital Object Identifier (DOI)

  • 10.1109/IEMBS.2010.5626466


  • eng

Conference Location

  • United States