Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/106432
Campo DC Valoridioma
dc.contributor.authorDionysio, Christinaen_US
dc.contributor.authorWild, Danielen_US
dc.contributor.authorPepe, Antonioen_US
dc.contributor.authorGsaxner, Christinaen_US
dc.contributor.authorLi, Jianningen_US
dc.contributor.authorAlvarez, Luisen_US
dc.contributor.authorEgger, Janen_US
dc.date.accessioned2021-04-05T14:57:05Z-
dc.date.available2021-04-05T14:57:05Z-
dc.date.issued2021en_US
dc.identifier.isbn978-151064031-3en_US
dc.identifier.issn1605-7422en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/106432-
dc.description.abstractDownloading of the abstract is permitted for personal use only.A practical method to analyze blood vessels, like the aorta, is to calculate the vessel's centerline and evaluate its shape in a CT or CTA scan. This contribution introduces a cloud-based centerline tool for the aorta, which computes an initial centerline from a CTA scan with two user given seed points. Afterwards, this initial centerline can be smoothed in a second step. The work done for this contribution was implemented into an existing online tool for medical image analysis, called Studierfenster. In order to evaluate the outcome of this contribution, we tested the smoothed centerline computed within Studierfenster against 40 baseline centerlines from a public available CTA challenge dataset. In doing so, we computed a minimum, maximum, and mean distance between the two centerlines in mm for every data sample, resulting in the smallest distance of 0.59mm, an overall maximum distance of 14.18mm, and a mean distance for all samples of 3.86mm with a standard deviation of 0.99mm.en_US
dc.languageengen_US
dc.relation.ispartofProgress in Biomedical Optics and Imaging - Proceedings of SPIEen_US
dc.sourceProgress in Biomedical Optics and Imaging - Proceedings of SPIE [ISSN 1605-7422], v. 11601, (Enero 2021)en_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.subject120601 Construcción de algoritmosen_US
dc.subject220990 Tratamiento digital. Imágenesen_US
dc.subject.otherAortaen_US
dc.subject.otherCalculationen_US
dc.subject.otherCenterlineen_US
dc.subject.otherClient/Serveren_US
dc.subject.otherStudierfensteren_US
dc.subject.otherTrackingen_US
dc.titleA cloud-based centerline algorithm for Studierfensteren_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conferenceMedical Imaging 2021en_US
dc.identifier.doi10.1117/12.2588268en_US
dc.identifier.scopus85103215398-
dc.contributor.authorscopusid57222554124-
dc.contributor.authorscopusid57213606134-
dc.contributor.authorscopusid57190872578-
dc.contributor.authorscopusid57202292092-
dc.contributor.authorscopusid57218473641-
dc.contributor.authorscopusid57222559257-
dc.contributor.authorscopusid23388906400-
dc.relation.volume11601en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.date.coverdateEnero 2021en_US
dc.identifier.conferenceidevents128432-
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INFen_US
dc.description.sjr0,246
dc.description.sjrq-
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR Modelos Matemáticos-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-6953-9587-
crisitem.author.parentorgDepartamento de Informática y Sistemas-
crisitem.author.fullNameÁlvarez León, Luis Miguel-
Colección:Actas de congresos
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