Symptoms Detection in Eye Retina Image

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F17%3APU126453" target="_blank" >RIV/00216305:26230/17:PU126453 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/11531/" target="_blank" >https://www.fit.vut.cz/research/publication/11531/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SSCI.2017.8285165" target="_blank" >10.1109/SSCI.2017.8285165</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Symptoms Detection in Eye Retina Image

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Symptoms Detection in Eye Retina Image

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2017 IEEE Symposium Series on Computational Intelligence

ISBN

978-1-5386-4058-6

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

3088-3093

Název nakladatele

IEEE Computer Society

Místo vydání

Hawaii

Místo konání akce

Hawaii, USA

Datum konání akce

27. 11. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000428251403022