Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/47460
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dc.contributor.authorRuiz-Alzola, J.en_US
dc.contributor.authorWestin, C. F.en_US
dc.contributor.authorWarfield, S. K.en_US
dc.contributor.authorAlberola, C.en_US
dc.contributor.authorMaier, S.en_US
dc.contributor.authorKikinis, R.en_US
dc.date.accessioned2018-11-23T13:44:24Z-
dc.date.available2018-11-23T13:44:24Z-
dc.date.issued2002en_US
dc.identifier.issn1361-8415en_US
dc.identifier.urihttp://hdl.handle.net/10553/47460-
dc.description.abstractNew medical imaging modalities offering multi-valued data, such as phase contrast MRA and diffusion tensor MM, require general representations for the development of automated algorithms. In this paper we propose a unified framework for the registration of medical volumetric multi-valued data using local matching. The paper extends the usual concept of similarity between two pieces of data to be matched, commonly used with scalar (intensity) data, to the general tensor case. Our approach to registration is based on a multiresolution scheme, where the deformation field estimated in a coarser level is propagated to provide an initial deformation in the next finer one. In each level, local matching of areas with a high degree of local structure and subsequent interpolation are performed. Consequently, we provide an algorithm to assess the amount of structure in generic multi-valued data by means of gradient and correlation computations. The interpolation step is carried out by means of the Kriging estimator, which provides a novel framework for the interpolation of sparse vector fields in medical applications. The feasibility of the approach is illustrated by results on synthetic and clinical data. (C) 2002 Elsevier Science B.V. All rights reserved.en_US
dc.languageengen_US
dc.publisher1361-8415-
dc.relation.ispartofMedical Image Analysisen_US
dc.sourceMedical Image Analysis[ISSN 1361-8415],v. 6, p. 143-161en_US
dc.subject3314 Tecnología médicaen_US
dc.subject.otherDiffusion Tensoren_US
dc.subject.otherImage Registrationen_US
dc.subject.otherSimilarity Measuresen_US
dc.subject.otherPoint Landmarksen_US
dc.subject.otherHuman Brainen_US
dc.subject.otherMren_US
dc.subject.otherRegularizationen_US
dc.subject.otherAngiographyen_US
dc.subject.otherInformationen_US
dc.subject.otherOrientationen_US
dc.titleNonrigid registration of 3D tensor medical dataen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S1361-8415(02)00055-5en_US
dc.identifier.scopus0036624331-
dc.identifier.isi000176394300005-
dc.contributor.authorscopusid56614041800-
dc.contributor.authorscopusid35477140400-
dc.contributor.authorscopusid7005171959-
dc.contributor.authorscopusid55999734500-
dc.contributor.authorscopusid55423785900-
dc.contributor.authorscopusid7101859155-
dc.description.lastpage161en_US
dc.description.firstpage143en_US
dc.relation.volume6en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid920778-
dc.contributor.daisngid47947-
dc.contributor.daisngid38669-
dc.contributor.daisngid2978308-
dc.contributor.daisngid174923-
dc.contributor.daisngid13443-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Ruiz-Alzola, J-
dc.contributor.wosstandardWOS:Westin, CF-
dc.contributor.wosstandardWOS:Warfield, SK-
dc.contributor.wosstandardWOS:Alberola, C-
dc.contributor.wosstandardWOS:Maier, S-
dc.contributor.wosstandardWOS:Kikinis, R-
dc.date.coverdateJunio 2002en_US
dc.identifier.ulpgces
dc.description.jcr2,68
dc.description.jcrqQ1
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptTecnología Médica y Audiovisual-
crisitem.author.deptIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.deptSeñales y Comunicaciones-
crisitem.author.orcid0000-0002-3545-2328-
crisitem.author.parentorgIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.fullNameRuiz Alzola, Juan Bautista-
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