Publication Details

Symptoms Detection in Eye Retina Image

KOŠTIALIK Daniel, MARUNIAK Lukáš and DRAHANSKÝ Martin. Symptoms Detection in Eye Retina Image. In: 2017 IEEE Symposium Series on Computational Intelligence. Hawaii: IEEE Computer Society, 2018, pp. 1-6. ISBN 978-1-5386-2725-9.
Czech title
Detekce symptomů v obrazu sítnice oka
Type
conference paper
Language
english
Authors
Koštialik Daniel, Bc. (FIT BUT)
Maruniak Lukáš, Ing. (DITS FIT BUT)
Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D. (DITS FIT BUT)
Keywords

eye retina, symptoma, macula, optic disc, segmentation

Abstract

Diabetic retinopathy and age related macular degeneration are among the most common eye retina diseases, which cause partial or complete blindness. The purpose of this study is to design and implement software for automatic detection of symptoms from eye fundus images. The detection algorithm is based on segmentation methods and follow up analysis of segmented areas. Detection of retina objects such as optic disc, macula and blood vessels is important prior symptoms detection as they can adversely affect the results of the analysis. Total 259 images of four databases were analyzed and algorithm reaches more than 90 % average success rate. The software might be useful in combination with appropriate hardware and optic devices, and can find a practical application in global population screening.

Published
2018
Pages
1-6
Proceedings
2017 IEEE Symposium Series on Computational Intelligence
Conference
2017 IEEE Symposium Series on Computational Intelligence, Hawaii, USA, US
ISBN
978-1-5386-2725-9
Publisher
IEEE Computer Society
Place
Hawaii, US
DOI
UT WoS
000428251403022
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB11531,
   author = "Daniel Ko\v{s}tialik and Luk\'{a}\v{s} Maruniak and Martin Drahansk\'{y}",
   title = "Symptoms Detection in Eye Retina Image",
   pages = "1--6",
   booktitle = "2017 IEEE Symposium Series on Computational Intelligence",
   year = 2018,
   location = "Hawaii, US",
   publisher = "IEEE Computer Society",
   ISBN = "978-1-5386-2725-9",
   doi = "10.1109/SSCI.2017.8285165",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11531"
}
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