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Evolutionary mosaicking for high-resolution wide-field optical coherence tomography angiography

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dc.contributor.authorMartínez Río, Javier
dc.contributor.authorCarmona Suárez, Enrique Javier
dc.contributor.authorCancelas, Daniel
dc.contributor.authorJorge Novo, Jorge
dc.contributor.authorOrtega, Marcos
dc.date.accessioned2025-04-29T11:23:22Z
dc.date.available2025-04-29T11:23:22Z
dc.date.issued2025-04-23
dc.descriptionThe registered version of this article, first published in “Applied Soft Computing, vol. 176, 2025", is available online at the publisher's website: Elsevier, https://doi.org/10.1016/j.asoc.2025.113145 La versión registrada de este artículo, publicado por primera vez en “Applied Soft Computing, vol. 176, 2025", está disponible en línea en el sitio web del editor: Elsevier, https://doi.org/10.1016/j.asoc.2025.113145
dc.description.abstractOptical coherence tomography angiography (OCTA) is a noninvasive imaging modality that produces retinal blood flow images. However, the limited field of view (FOV) of typical high-resolution scan poses challenges for comprehensive analysis. This work presents a fully automatic method for generating high-resolution wide-field OCTA mosaics from overlapping scans, addressing the need for wider FOVs without requiring advanced OCTA equipment or manual mosaicking. The proposed approach consists of a three-stage pipeline: an initial mosaic is constructed using correlation-based template matching, refined with an evolutionary algorithm to optimize vascular continuity at seams, and finalized with a blending stage to improve overall quality. Unlike existing methods, our approach avoids keypoint extraction or input image preprocessing, making it robust against noise and artifacts typically present in clinical OCTA images. Using a correlation-based metric that measures the degree of vascular continuity at the seams in each mosaic, we obtained a mean and standard deviation equal to (before blending) for all the mosaics analyzed. The proposed method presented robust results, producing high-resolution wide-field OCTA mosaics.en
dc.description.versionversión publicada
dc.identifier.citationJavier Martínez-Río, Enrique J. Carmona, Daniel Cancelas, Jorge Novo, Marcos Ortega. Evolutionary mosaicking for high-resolution wide-field optical coherence tomography angiography. Applied Soft Computing, 113145, 2025. DOI: https://doi.org/10.1016/j.asoc.2025.113145
dc.identifier.doihttps://doi.org/10.1016/j.asoc.2025.113145
dc.identifier.issn1872-9681
dc.identifier.urihttps://hdl.handle.net/20.500.14468/26506
dc.journal.titleApplied Soft Computing
dc.journal.volume176
dc.language.isoen
dc.page.initial113145
dc.publisherELSEVIER
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentInteligencia Artificial
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.es
dc.subject33 Ciencias Tecnológicas
dc.subject.keywordswide-field OCTAen
dc.subject.keywordsretinal mosaickingen
dc.subject.keywordsmulti-image registrationen
dc.subject.keywordstemplate matchingen
dc.subject.keywordsdifferential evolutionen
dc.subject.keywordsalpha blendingen
dc.titleEvolutionary mosaicking for high-resolution wide-field optical coherence tomography angiographyen
dc.typeartículoes
dc.typejournal articleen
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relation.isAuthorOfPublication.latestForDiscovery5e870768-cc8e-47fe-9662-25cd1385fd3c
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