Distinguishing true retinal area from artefacts in SLO images is a challenging task, which is the first important step towards computeraided disease diagnosis. In this paper, we have developed a new method based on superpixel feature analysis and classification approaches for determination of retinal area scanned by Scanning Laser Ophthalmoscope(SLO). Our prototype has achieved the accuracy of 90% on healthy as well as diseased retinal images. To the best of our knowledge, this is the first work on retinal area detection in SLO images.
Published in
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Volume
8671Pages
254 - 261Citation
HALEEM, M.S. ... et al, 2014. Superpixel based retinal area detection in SLO images. IN: Chmielewski, L.J. ... et al (eds). Computer Vision and Graphics: International Conference, ICCVG 2014, Warsaw, Poland, September 15-17, 2014. Proceedings. Lecture Notes in Computer Science, 8671, pp.254-261Publisher
Springer International Publishing (© Springer International Publishing Switzerland)Version
VoR (Version of Record)Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2014Notes
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-11331-9_31ISBN
9783319113302;9783319113319ISSN
0302-9743eISSN
1611-3349Language
en
CC BY-NC-ND 4.0