Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/69951
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dc.contributor.authorAlvarez, Luisen_US
dc.contributor.authorSantana-Cedrés, Danielen_US
dc.contributor.authorTahoces, Pablo G.en_US
dc.contributor.authorCarreira, José M.en_US
dc.date.accessioned2020-02-05T12:51:31Z-
dc.date.available2020-02-05T12:51:31Z-
dc.date.issued2019en_US
dc.identifier.isbn978-3-030-22367-0en_US
dc.identifier.issn0302-9743en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/69951-
dc.description.abstractIn this work we present an application of variational techniques to the smoothing and registration of aorta centerlines. We assume that a 3D segmentation of the aorta lumen and an initial estimation of the aorta centerline are available. The centerline smoothing technique aims to maximize the distance of the centerline to the boundary of the aorta lumen segmentation but keeping the curve smooth. The proposed registration technique computes a rigid transformation by minimizing the squared Euclidean distance between the points of the curves, using landmarks and taking into account that the curves can be of different lengths. We present a variety of experiments on synthetic and real scenarios in order to show the performance of the methods.en_US
dc.languageengen_US
dc.publisherSpringeren_US
dc.relationNuevos Modelos Matemáticos Para la Segmentación y Clasificación en Imágenesen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceScale Space and Variational Methods in Computer Vision. SSVM 2019. Lecture Notes in Computer Science, v. 11603 LNCS, p. 447-458en_US
dc.subject220990 Tratamiento digital. Imágenesen_US
dc.subject.other3D Curve Registrationen_US
dc.subject.other3D Curve Smoothingen_US
dc.subject.otherAorta Centerlineen_US
dc.subject.otherVariational Methodsen_US
dc.titleAorta centerline smoothing and registration using variational modelsen_US
dc.typeinfo:eu-repo/semantics/bookParten_US
dc.typeBook parten_US
dc.relation.conference7th International Conference on Scale Space and Variational Methods in Computer Vision, (SSVM 2019)en_US
dc.identifier.doi10.1007/978-3-030-22368-7_35en_US
dc.identifier.scopus85068465057-
dc.contributor.authorscopusid55640159000-
dc.contributor.authorscopusid54974008500-
dc.contributor.authorscopusid6603850497-
dc.contributor.authorscopusid7006788384-
dc.description.lastpage458en_US
dc.description.firstpage447en_US
dc.relation.volume11603en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Capítulo de libroen_US
dc.utils.revisionen_US
dc.identifier.supplement0302-9743-
dc.identifier.supplement0302-9743-
dc.identifier.conferenceidevents121656-
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INFen_US
dc.contributor.buulpgcBU-INFen_US
dc.contributor.buulpgcBU-INFen_US
dc.contributor.buulpgcBU-INFen_US
dc.description.sjr0,427
dc.description.sjrqQ2
dc.description.spiqQ1
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.project.principalinvestigatorÁlvarez León, Luis Miguel-
crisitem.author.deptGIR Modelos Matemáticos-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Centro de Tecnologías de la Imagen-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-6953-9587-
crisitem.author.orcid0000-0003-2032-5649-
crisitem.author.parentorgDepartamento de Informática y Sistemas-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.fullNameÁlvarez León, Luis Miguel-
crisitem.author.fullNameSantana Cedrés, Daniel Elías-
crisitem.event.eventsstartdate30-06-2019-
crisitem.event.eventsenddate04-07-2019-
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