Identification of the optic nerve head with genetic algorithms

Carmona, Enrique J., Rincón, Mariano, García Feijoó, Julián y Martínez de la Casa, José M. . (2008) Identification of the optic nerve head with genetic algorithms. Artificial Intelligence in Medicine 43(3), 243-259 (2008)

Ficheros (Some files may be inaccessible until you login with your e-spacio credentials)
Nombre Descripción Tipo MIME Size
Carmona_Suarez_Enrique_IDENTIFICATION_ON_OPTIC.pdf Carmona_Suarez_Enrique_IDENTIFICATION_ON OPTIC.pdf application/pdf 458.97KB

Título Identification of the optic nerve head with genetic algorithms
Autor(es) Carmona, Enrique J.
Rincón, Mariano
García Feijoó, Julián
Martínez de la Casa, José M.
Materia(s) Informática
Ingeniería Informática
Abstract Objective This work proposes creating an automatic system to locate and segment the optic nerve head (ONH) in eye fundus photographic images using genetic algorithms. Methods and material Domain knowledge is used to create a set of heuristics that guide the various steps involved in the process. Initially, using an eye fundus colour image as input, a set of hypothesis points was obtained that exhibited geometric properties and intensity levels similar to the ONH contour pixels. Next, a genetic algorithm was used to find an ellipse containing the maximum number of hypothesis points in an offset of its perimeter, considering some constraints. The ellipse thus obtained is the approximation to the ONH. The segmentation method is tested in a sample of 110 eye fundus images, belonging to 55 patients with glaucoma (23.1%) and eye hypertension (76.9%) and random selected from an eye fundus image base belonging to the Ophthalmology Service at Miguel Servet Hospital, Saragossa (Spain). Results and conclusions The results obtained are competitive with those in the literature. The method's generalization capability is reinforced when it is applied to a different image base from the one used in our study and a discrepancy curve is obtained very similar to the one obtained in our image base. In addition, the robustness of the method proposed can be seen in the high percentage of images obtained with a discrepancy δ < 5 (96% and 99% in our and a different image base, respectively). The results also confirm the hypothesis that the ONH contour can be properly approached with a non-deformable ellipse. Another important aspect of the method is that it directly provides the parameters characterising the shape of the papilla: lengths of its major and minor axes, its centre of location and its orientation with regard to the horizontal position.
Palabras clave Optic nerve head segmentation
Genetic algorithm
Constraint handling
Ellipse fitting
Editor(es) Elsevier
Fecha 2008-07
Formato application/pdf
Identificador bibliuned:95-Ejcarmona-0016
DOI - identifier
ISSN - identifier 1873-2860
Nombre de la revista Artificial Intelligence in Medicine
Número de Volumen 43
Número de Issue 3
Página inicial 243
Página final 259
Publicado en la Revista Artificial Intelligence in Medicine 43(3), 243-259 (2008)
Idioma eng
Versión de la publicación acceptedVersion
Tipo de recurso Article
Derechos de acceso y licencia
Tipo de acceso Acceso abierto
Notas adicionales This is an Accepted Manuscript of an article published by Elsevier in "Artificial Intelligence in Medicine 43(3), 243-259 (2008)", available at:
Notas adicionales Este es el manuscrito aceptado del artículo publicado por Elsevier en "Artificial Intelligence in Medicine 43(3), 243-259 (2008)", disponible en:

Versión Tipo de filtro
Contador de citas: Google Scholar Search Google Scholar
Estadísticas de acceso: 55 Visitas, 15 Descargas  -  Estadísticas en detalle
Creado: Thu, 11 Apr 2024, 18:15:07 CET