Scopus: 15 citations, Google Scholar: citations
Automatic Segmentation of Optic Disc in Eye Fundus Images : a Survey
Allam, Ali (Arab Academy for Science, Technology and Maritime Transport)
Youssif, Aliaa (Helwan University)
Ghalwash, Atef (Helwan University)

Date: 2015
Abstract: Optic disc detection and segmentation is one of the key elements for automatic retinal disease screening systems. The aim of this survey paper is to review, categorize and compare the optic disc detection algorithms and methodologies, giving a description of each of them, highlighting their key points and performance measures. Accordingly, this survey firstly overviews the anatomy of the eye fundus showing its main structural components along with their properties and functions. Consequently, the survey reviews the image enhancement techniques and also categorizes the image segmentation methodologies for the optic disc which include property-based methods, methods based on convergence of blood vessels, and model-based methods. The performance of segmentation algorithms is evaluated using a number of publicly available databases of retinal images via evaluation metrics which include accuracy and true positive rate (i. e. sensitivity). The survey, at the end, describes the different abnormalities occurring within the optic disc region.
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Language: Anglès
Document: Article ; recerca ; Versió publicada
Published in: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 14 núm. 1 (2015) , p. 1-20 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v14-n1-allam-youssif-chalwash
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/297642
DOI: 10.5565/rev/elcvia.680


17 p, 1.1 MB

The record appears in these collections:
Articles > Published articles > ELCVIA
Articles > Research articles

 Record created 2015-04-29, last modified 2022-02-13



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