Automatic detection of the macula in retinal fundus images using seeded mode tracking approach.

Published

Journal Article

The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5%, and 90.5% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.

Full Text

Duke Authors

Cited Authors

  • Wong, DWK; Liu, J; Tan, N-M; Yin, F; Cheng, X; Cheng, C-Y; Cheung, GCM; Wong, TY

Published Date

  • 2012

Published In

Volume / Issue

  • 2012 /

Start / End Page

  • 4950 - 4953

PubMed ID

  • 23367038

Pubmed Central ID

  • 23367038

International Standard Serial Number (ISSN)

  • 1557-170X

Digital Object Identifier (DOI)

  • 10.1109/EMBC.2012.6347103

Language

  • eng

Conference Location

  • United States