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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/20256

Title: Superpixel based retinal area detection in SLO images
Authors: Haleem, Muhammad Salman
Han, Liangxiu
van Hemert, Jano
Li, Baihua
Fleming, Alan
Keywords: Scanning Laser Ophthalmoscope
Fundus imaging
Retinal image analysis
Retinal artefacts extraction
Issue Date: 2014
Publisher: Springer International Publishing (© Springer International Publishing Switzerland)
Citation: 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.254-261
Abstract: 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.
Description: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-11331-9_31
Version: Published
DOI: 10.1007/978-3-319-11331-9_31
URI: https://dspace.lboro.ac.uk/2134/20256
Publisher Link: http://dx.doi.org/10.1007/978-3-319-11331-9_31
ISBN: 9783319113302
ISSN: 0302-9743
Appears in Collections:Conference Papers and Presentations (Computer Science)

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