Publication Details

Symptoms Detection in Eye Retina Image

KOŠTIALIK, D.; MARUNIAK, L.; DRAHANSKÝ, M. Symptoms Detection in Eye Retina Image. In 2017 IEEE Symposium Series on Computational Intelligence. Hawaii: IEEE Computer Society, 2018. p. 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.
Maruniak Lukáš, Ing.
Drahanský Martin, prof. Ing., Ph.D.

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.

Annotation

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 thesis is to design and implement software for automatic
detection of symptoms from eye fundus images. The detection algorithm is based
on segmentation methods and afterwards analysis. Determination 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 may be useful in combination with appropriate
hardware and optic mechanism, which forms one of practical application in global
population screening.

Published

2018

Pages

1–6

Proceedings

2017 IEEE Symposium Series on Computational Intelligence

ISBN

978-1-5386-2725-9

Publisher

IEEE Computer Society

Place

Hawaii

DOI

10.1109/SSCI.2017.8285165

UT WoS

000428251403022

EID Scopus

2-s2.0-85046114801

BibTeX

@inproceedings{BUT144476,
  author="Daniel {Koštialik} and Lukáš {Maruniak} and Martin {Drahanský}",
  title="Symptoms Detection in Eye Retina Image",
  booktitle="2017 IEEE Symposium Series on Computational Intelligence",
  year="2018",
  pages="1--6",
  publisher="IEEE Computer Society",
  address="Hawaii",
  doi="10.1109/SSCI.2017.8285165",
  isbn="978-1-5386-2725-9",
  url="https://www.fit.vut.cz/research/publication/11531/"
}