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 inLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages254 - 261
CitationHALEEM, 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.254-261
PublisherSpringer International Publishing (© Springer International Publishing Switzerland)
VersionVoR (Version of Record)
Publisher statementThis 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/
NotesThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-11331-9_31