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Detection of Early Signs of Diabetic Retinopathy Based on Textural and Morphological Information in Fundus Images

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Detection of Early Signs of Diabetic Retinopathy Based on Textural and Morphological Information in Fundus Images

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dc.contributor.author Colomer, Adrián es_ES
dc.contributor.author Igual García, Jorge es_ES
dc.contributor.author Naranjo Ornedo, Valeriana es_ES
dc.date.accessioned 2021-09-09T03:34:29Z
dc.date.available 2021-09-09T03:34:29Z
dc.date.issued 2020-02 es_ES
dc.identifier.uri http://hdl.handle.net/10251/171678
dc.description.abstract [EN] Estimated blind people in the world will exceed 40 million by 2025. To develop novel algorithms based on fundus image descriptors that allow the automatic classification of retinal tissue into healthy and pathological in early stages is necessary. In this paper, we focus on one of the most common pathologies in the current society: diabetic retinopathy. The proposed method avoids the necessity of lesion segmentation or candidate map generation before the classification stage. Local binary patterns and granulometric profiles are locally computed to extract texture and morphological information from retinal images. Different combinations of this information feed classification algorithms to optimally discriminate bright and dark lesions from healthy tissues. Through several experiments, the ability of the proposed system to identify diabetic retinopathy signs is validated using different public databases with a large degree of variability and without image exclusion. es_ES
dc.description.sponsorship This work has been partially supported by the Spanish Ministry of Economy and Competitiveness through project DPI2016-77869 and GVA through project PROMETEO/2019/109 es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Sensors es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Biomedical image processing es_ES
dc.subject Diabetic retinopathy es_ES
dc.subject Classification es_ES
dc.subject Granulometry-based descriptor es_ES
dc.subject LBP es_ES
dc.subject Hand-driven learning es_ES
dc.subject Exudates es_ES
dc.subject Microaneurysms es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.title Detection of Early Signs of Diabetic Retinopathy Based on Textural and Morphological Information in Fundus Images es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s20041005 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//DPI2016-77869-C2-1-R/ES/SISTEMA DE INTERPRETACION DE IMAGENES HISTOPATOLOGICAS PARA LA DETECCION DE CANCER DE PROSTATA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2019%2F109/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Colomer, A.; Igual García, J.; Naranjo Ornedo, V. (2020). Detection of Early Signs of Diabetic Retinopathy Based on Textural and Morphological Information in Fundus Images. Sensors. 20(4):1-20. https://doi.org/10.3390/s20041005 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/s20041005 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 20 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 20 es_ES
dc.description.issue 4 es_ES
dc.identifier.eissn 1424-8220 es_ES
dc.identifier.pmid 32069912 es_ES
dc.identifier.pmcid PMC7071097 es_ES
dc.relation.pasarela S\402742 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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