Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/53334
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dc.contributor.authorBalocco, Simone-
dc.contributor.authorGatta, Carlo-
dc.contributor.authorCiompi, Francesco-
dc.contributor.authorWahle, Andreas-
dc.contributor.authorRadeva, Petia-
dc.contributor.authorCarlier, Stéphane-
dc.contributor.authorÜnal, Gözde B.-
dc.contributor.authorSanidas, Elias-
dc.contributor.authorMauri, Josepa-
dc.contributor.authorCarrillo, Xavier-
dc.contributor.authorKovarnik, Tomas-
dc.contributor.authorWang, Ching-Wei-
dc.contributor.authorChen, Hsiang-Chou-
dc.contributor.authorExarchos, Themis P.-
dc.contributor.authorFotiadis, Dimitrios I.-
dc.contributor.authorDestrempes, François-
dc.contributor.authorCloutier, Guy-
dc.contributor.authorPujol Vila, Oriol-
dc.contributor.authorAlberti, Marina-
dc.contributor.authorMendizabal-Ruiz, E. Gerardo-
dc.date.accessioned2014-04-08T09:30:57Z-
dc.date.available2014-04-08T09:30:57Z-
dc.date.issued2014-03-
dc.identifier.issn0895-6111-
dc.identifier.urihttp://hdl.handle.net/2445/53334-
dc.description.abstractThis paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.-
dc.format.extent21 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherElsevier Ltd-
dc.relation.isformatofVersió postprint del document publicat a: 10.1016/j.compmedimag.2013.07.001-
dc.relation.ispartofComputerized Medical Imaging and Graphics, 2014, vol. 38, num. 2, p. 70-90-
dc.relation.urihttp://dx.doi.org/10.1016/j.compmedimag.2013.07.001-
dc.rights(c) Elsevier Ltd, 2014-
dc.sourceArticles publicats en revistes (Matemàtiques i Informàtica)-
dc.subject.classificationUltrasons en medicina-
dc.subject.classificationImatges mèdiques-
dc.subject.classificationInformàtica mèdica-
dc.subject.classificationAlgorismes computacionals-
dc.subject.otherUltrasonics in medicine-
dc.subject.otherImaging systems in medicine-
dc.subject.otherMedical informatics-
dc.subject.otherComputer algorithms-
dc.titleStandardized evaluation methodology and reference database for evaluating IVUS image segmentation-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/acceptedVersion-
dc.identifier.idgrec638857-
dc.date.updated2014-04-08T09:30:57Z-
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/224297/EU//ARTREAT-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
Appears in Collections:Articles publicats en revistes (Matemàtiques i Informàtica)
Publicacions de projectes de recerca finançats per la UE

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