Affiliations 

  • 1 Department of Electronic and Computer Engineering (ECE), Ngee Ann Polytechnic, Singapore g.karthikeya@gmail.com
  • 2 Department of Electronic and Computer Engineering (ECE), Ngee Ann Polytechnic, Singapore Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
  • 3 Department of Electronic and Computer Engineering (ECE), Ngee Ann Polytechnic, Singapore
  • 4 National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore
Proc Inst Mech Eng H, 2014 Sep;228(9):962-70.
PMID: 25234036 DOI: 10.1177/0954411914550847

Abstract

Identification of retinal landmarks is an important step in the extraction of anomalies in retinal fundus images. In the current study, we propose a technique to identify and localize the position of macula and hence the fovea avascular zone, in colour fundus images. The proposed method, based on varying blur scales in images, is independent of the location of other anatomical landmarks present in the fundus images. Experimental results have been provided using the open database MESSIDOR by validating our segmented regions using the dice coefficient, with ground truth segmentation provided by a human expert. Apart from testing the images on the entire MESSIDOR database, the proposed technique was also validated using 50 normal and 50 diabetic retinopathy chosen digital fundus images from the same database. A maximum overlap accuracy of 89.6%-93.8% and locational accuracy of 94.7%-98.9% was obtained for identification and localization of the fovea.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.