Superpixel based retinal area detection in SLO images

被引：0
|
作者：
Haleem, Muhammad Salman [1 ]
Han, Liangxiu [1 ]
van Hemert, Jano [2 ]
Li, Baihua [1 ]
Fleming, Alan [2 ]
机构：
[1] School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Chester Street, Manchester,M1 5GD, United Kingdom
[2] Optos plc, Queensferry House, Carnegie Business Campus, Enterprise Way, Dunfermline,KY11 8GR, United Kingdom
来源：
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2014年 / 8671卷
关键词：
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. © Springer International Publishing Switzerland 2014;
D O I：
10.1007/978-3-319-11331-9_31
中图分类号：
学科分类号：
摘要：
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页码：254 / 261
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