DETECTION AND SEGMENTATION OF RETINAL LESIONS IN RETCAM 3 IMAGES BASED ON ACTIVE CONTOURS DRIVEN BY STATISTICAL LOCAL FEATURES

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10242724" target="_blank" >RIV/61989100:27240/19:10242724 - isvavai.cz</a>

Result on the web

<a href="http://advances.utc.sk/index.php/AEEE/article/view/3045/488488572" target="_blank" >http://advances.utc.sk/index.php/AEEE/article/view/3045/488488572</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15598/aeee.v17i2.3045" target="_blank" >10.15598/aeee.v17i2.3045</a>

Result language

angličtina

Original language name

DETECTION AND SEGMENTATION OF RETINAL LESIONS IN RETCAM 3 IMAGES BASED ON ACTIVE CONTOURS DRIVEN BY STATISTICAL LOCAL FEATURES

Original language description

Clinical retinal image analysis is an import aspect of clinical diagnosis in ophthalmology. Retinopathy of Prematurity (ROP) represents one of the most severe retinal disorders in prematurely born infants. One of the ROP clinical signs is the presence of retinal lesions endangering the vision system. Unfortunately, the stage and progress of these findings is often only subjectively estimated. A procedure such as this is undoubtedly linked to subjective inaccuracies depending on the experience of the ophthalmologist. In our study, a fully autonomous segmentation algorithm to model retinal lesions found using RetCam 3 is proposed. The proposed method used a combination of retinal image preprocessing and active contours for retinal lesion segmentation. Based on this procedure, a binary model of retinal lesions that allowed retinal lesions to be classified from a retinal image background was obtained. Another important aspect of the model was feature extraction. These features reliably and automatically described the development stage of an individual lesion. A complex procedure such as this has significant implications for ophthalmic clinical practice in substituting manual clinical procedures and improving the accuracy of routine clinical decisions.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

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

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

Publication year

2019

Confidentiality

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

Name of the periodical

Advances in Electrical and Electronic Engineering

ISSN

1336-1376

e-ISSN

—

Volume of the periodical

17

Issue of the periodical within the volume

2

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

8

Pages from-to

194-201

UT code for WoS article

000472599800012

EID of the result in the Scopus database

2-s2.0-85068460064