Computer-aided glaucoma diagnosis using stochastic watershed transformation on single fundus images

dc.centroUniversidad Cardenal Herrera-CEU
dc.contributor.authorDíaz Pinto, Andrés
dc.contributor.authorMorales Martínez, Sandra
dc.contributor.authorNaranjo Ornedo, Valeriana
dc.contributor.authorNavea Tejerina, Amparo
dc.contributor.otherProducción Científica UCH 2019
dc.contributor.otherUCH. Departamento de Medicina y Cirugía
dc.date2019
dc.date.accessioned2020-09-16T04:00:17Z
dc.date.available2020-09-16T04:00:17Z
dc.date.issued2019-08-01
dc.descriptionEl 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
dc.descriptionEste 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
dc.descriptionThis 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
dc.description.abstractGlaucoma 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.
dc.formatapplication/pdf
dc.identifier.citationDíaz-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
dc.identifier.doihttps://doi.org/10.1166/jmihi.2019.2721
dc.identifier.issn2156-7018
dc.identifier.issn2156-7026 (Electrónico)
dc.identifier.urihttp://hdl.handle.net/10637/11659
dc.language.isoen
dc.publisherAmerican Scientific Publishers.
dc.relationEste trabajo fue financiado por el proyecto GALAHAD (H2020-ICT-2016-2017, 732613). El trabajo de Andrés Díaz-Pinto fue financiado por la Generalitat Valenciana a través de una beca Santiago Grisolía (GRISOLIA /2015/027).
dc.relation.ispartofJournal of Medical Imaging and Health Informatics, vol. 9, n. 6 (aug. 2019)
dc.relation.projectIDH2020-ICT-2016-2017, 732613
dc.relation.projectIDGRISOLIA /2015/027
dc.rightsopen access
dc.rights.cchttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subjectGlaucoma - Diagnosis - Mathematical models.
dc.subjectOjos - Enfermedades - Diagnóstico - Modelos matemáticos.
dc.subjectGlaucoma - Diagnóstico - Modelos matemáticos.
dc.subjectEye - Diseases - Diagnosis - Mathematical models.
dc.titleComputer-aided glaucoma diagnosis using stochastic watershed transformation on single fundus images
dc.typeArtículo
dspace.entity.typePublicationes

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