Revista: | Latin-American Journal of Computing (LAJC) |
Base de datos: | PERIÓDICA |
Número de sistema: | 000448814 |
ISSN: | 1390-9134 |
Autores: | Intriago Pazmiño, Monserrate1 Uyaguari Uyaguari, Fernando1 Salazar Jácome, Elizabeth2 |
Instituciones: | 1Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingenieros Informáticos, Madrid. España 2Universidad de las Fuerzas Armadas, Jefatura de Investigación y Vinculación con la Colectividad, Latacunga, Cotopaxi. Ecuador |
Año: | 2014 |
Volumen: | 1 |
Número: | 1 |
Paginación: | 37-42 |
País: | Ecuador |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Aplicado, descriptivo |
Resumen en inglés | This paper presents a review of algorithms for extracting blood vessels network from retinal images. Since retina is a complex and delicate ocular structure, a huge effort in computer vision is devoted to study blood vessels network for helping the diagnosis of pathologies like diabetic retinopathy, hypertension retinopathy, retinopathy of prematurity or glaucoma. To carry out this process many works for normal and abnormal images have been proposed recently. These methods include combinations of algorithms like Gaussian and Gabor filters, histogram equalization, clustering, binarization, motion contrast, matched filters, combined corner/edge detectors, multi-scale line operators, neural networks, ants, genetic algorithms, morphological operators. To apply these algorithms pre-processing tasks are needed. Most of these algorithms have been tested on publicly retinal databases. We have include a table summarizing algorithms and results of their assessment |
Disciplinas: | Ciencias de la computación, Medicina |
Palabras clave: | Oftalmología, Procesamiento de datos, Retina, Vascularización, Fondo de ojo, Retinopatía, Segmentación de imágenes, Análisis de imágenes |
Keyword: | Ophthalmology, Data processing, Retina, Vascularization, Fundus oculi, Image analysis, Retinopathy, Image segmentation |
Texto completo: | Texto completo (Ver PDF) |