- No file added yet -
Superpixel based retinal area detection in SLO images
journal contribution
posted on 2016-02-08, 16:15 authored by Muhammad Salman Haleem, Liangxiu Han, Jano van Hemert, Baihua LiBaihua Li, Alan FlemingDistinguishing 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.
History
School
- Science
Department
- Computer Science
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
1611-3349Publisher version
Language
- en
