Self-assessment for optic disc segmentation

Conference Paper

Optic disc segmentation from retinal fundus image is a fundamental but important step in many applications such as automated glaucoma diagnosis. Very often, one method might work well on many images but fail on some other images and it is difficult to have a single method or model to cover all scenarios. Therefore, it is important to combine results from several methods to minimize the risk of failure. For this purpose, this paper computes confidence scores for three methods and combine their results for an optimal one. The experimental results show that the combined result from three methods is better than the results by any individual method. It reduces the mean overlapping error by 7.4% relatively compared with best individual method. Simultaneously, the number of failed cases with large overlapping errors is also greatly reduced. This is important to enhance the clinical deployment of the automated disc segmentation. © 2013 IEEE.

Full Text

Duke Authors

Cited Authors

  • Cheng, J; Liu, J; Yin, F; Lee, BH; Wong, DWK; Aung, T; Cheng, CY; Wong, TY

Published Date

  • October 31, 2013

Published In

Start / End Page

  • 5861 - 5864

International Standard Serial Number (ISSN)

  • 1557-170X

International Standard Book Number 13 (ISBN-13)

  • 9781457702167

Digital Object Identifier (DOI)

  • 10.1109/EMBC.2013.6610885

Citation Source

  • Scopus