Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images

Clicks: 208
ID: 29346
2017
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #116 of 189 articles by views in PeerJ

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 189 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
A new method for automatic optic disc localization and segmentation is presented. The localization procedure combines vascular and brightness information to provide the best estimate of the optic disc center which is the starting point for the segmentation algorithm. A detection rate of 99.58% and 100% was achieved for the Messidor and ONHSD databases, respectively. A simple circular approximation to the optic disc boundary is proposed based on the maximum average contrast between the inner and outer ring of a circle centered on the estimated location. An average overlap coefficient of 0.890 and 0.865 was achieved for the same datasets, outperforming other state of the art methods. The results obtained confirm the advantages of using a simple circular model under non-ideal conditions as opposed to more complex deformable models.
Reference Key
sigut2017contrastpeerj Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Sigut, Jose;Nunez, Omar;Fumero, Francisco;Gonzalez, Marta;Arnay, Rafael;
Journal PeerJ
Year 2017
DOI
DOI not found
URL
https://peerj.com/articles/3763.pdf
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.