Standardized evaluation methodology and reference database for evaluating IVUS image segmentation

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.date.updated2014-04-08T09:30:57Z
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.identifier.idgrec638857
dc.identifier.issn0895-6111
dc.identifier.urihttps://hdl.handle.net/2445/53334
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.projectIDinfo:eu-repo/grantAgreement/EC/FP7/224297/EU//ARTREAT
dc.relation.urihttp://dx.doi.org/10.1016/j.compmedimag.2013.07.001
dc.rights(c) Elsevier Ltd, 2014
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
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

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