Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10637/11659
Título : Computer-aided glaucoma diagnosis using stochastic watershed transformation on single fundus images
Autor : Díaz Pinto, Andrés.
Morales Martínez, Sandra.
Naranjo Ornedo, Valeriana.
Navea Tejerina, Amparo.
Materias: Glaucoma - Diagnosis - Mathematical models.Ojos - Enfermedades - Diagnóstico - Modelos matemáticos.Glaucoma - Diagnóstico - Modelos matemáticos.Eye - Diseases - Diagnosis - Mathematical models.
Fecha de publicación : 1-ago-2019
Editorial : American Scientific Publishers.
Citación : Díaz-Pinto, AY., Morales, S., Naranjo Ornedo, V. & Navea, A. (2019). Computer-aided glaucoma diagnosis using stochastic watershed transformation on single fundus images. Journal of Medical Imaging and Health Informatics, vol. 9, i. 6, pp. 1057-1065. DOI: https://doi.org/10.1166/jmihi.2019.2721
Resumen : Glaucoma is a chronic eye disease and one of the major causes of permanent blindness. Since it does not show initial symptoms, early diagnosis is important to limit its progression. This paper presents an automatic optic nerve characterization algorithm for glaucoma diagnosis based only on retinal fundus images. For optic cup segmentation, we used a new method based on the stochastic watershed transformation applied on the YIQ colour space to extract clinical indicators such as the Cup/Disc ratio, the area Cup/Disc ratio and the ISNT rule. Afterwards, an assessment between normal and glaucomatous fundus images is performed. The proposed algorithm was evaluated on 6 di erent (private and public) databases containing 723 images (377 normal and 346 glaucomatous images) which achieved a specificity and sensitivity of 0.674 and 0.675, respectively. Moreover, an F-score of 0:770 was obtained when evaluating this method on the publicly available database Drishti-GS1. A comparison of the proposed work with other state-of-the-art methods demonstrates the robustness of the proposed algorithm; because it was tested using images from di erent databases with high variability, which is a common issue in this area. Additional comparisons with existing works for cup segmentation, that use the publicly available database Drishti-GS1, are also presented in this paper.
Descripción : El resumen de este artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.ingentaconnect.com/content/asp/jmihi/2019/00000009/00000006/art00001
Este es el pre-print del siguiente artículo: Díaz-Pinto, AY., Morales, S., Naranjo Ornedo, V. & Navea, A. (2019). Computer-aided glaucoma diagnosis using stochastic watershed transformation on single fundus images. Journal of Medical Imaging and Health Informatics, vol. 9, i. 6, pp. 1057-1065, que se ha publicado de forma definitiva en https://doi.org/10.1166/jmihi.2019.2721
This is the pre-peer reviewed version of the following article: Díaz-Pinto, AY., Morales, S., Naranjo Ornedo, V. & Navea, A. (2019). Computer-aided glaucoma diagnosis using stochastic watershed transformation on single fundus images. Journal of Medical Imaging and Health Informatics, vol. 9, i. 6, pp. 1057-1065, which has been published in final form at https://doi.org/10.1166/jmihi.2019.2721
URI : http://hdl.handle.net/10637/11659
Derechos: http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
ISSN : 2156-7018
2156-7026 (Electrónico)
Aparece en las colecciones: Dpto. Medicina y Cirugía

Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
Computer-aided_Diaz_JMIHI_2019.pdf1,74 MBAdobe PDFVisualizar/Abrir



Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.