Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/339357
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampPedrini, Hélio-
dc.typeArtigopt_BR
dc.titleMedical image interpolation based on 3D Lanczos filteringpt_BR
dc.contributor.authorMoraes, Thiago-
dc.contributor.authorAmorim, Paulo-
dc.contributor.authorSilva, Jorge Vicente Da-
dc.contributor.authorPedrini, Helio-
dc.subjectInterpolaçãopt_BR
dc.subject.otherlanguageInterpolationpt_BR
dc.description.abstractSeveral medical imaging techniques have been employed to create visual representations of internal anatomic structures, such as organs and tissues, for clinical procedures. Diagnosis and treatment of diseases have benefited from the use of imaging modalities, such as computed tomography, magnetic resonance imaging, ultrasonography, mammography, and photon emission tomography. Interpolation is a method for generating new data points on a regular grid from a set of known data points, as result of some image transformations, such as scaling and rotation. Several filters have been proposed to implement image interpolation. In this paper, we develop and evaluate a resampling method based on the three-dimensional Lanczos kernel. Experiments are conducted on several medical images and videos to demonstrate the effectiveness of the proposed interpolation approachpt_BR
dc.relation.ispartofComputer methods in biomechanics and biomedical engineeringpt_BR
dc.publisher.cityAbingdonpt_BR
dc.publisher.countryReino Unidopt_BR
dc.publisherTaylor & Francispt_BR
dc.date.issued2019-11-
dc.date.monthofcirculationNov.pt_BR
dc.language.isoengpt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn2168-1163pt_BR
dc.identifier.eissn2168-1171pt_BR
dc.identifier.doi10.1080/21681163.2019.1683469pt_BR
dc.identifier.urlhttps://www.tandfonline.com/doi/full/10.1080/21681163.2019.1683469pt_BR
dc.description.sponsorshipCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQpt_BR
dc.description.sponsorshipFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPpt_BR
dc.description.sponsordocumentnumber309330/2018-1pt_BR
dc.description.sponsordocumentnumber2017/12646-3; 2014/12236-1pt_BR
dc.date.available2020-04-20T20:23:40Z-
dc.date.accessioned2020-04-20T20:23:40Z-
dc.description.provenanceSubmitted by Susilene Barbosa da Silva (susilene@unicamp.br) on 2020-04-20T20:23:40Z No. of bitstreams: 0. Added 1 bitstream(s) on 2020-07-30T19:34:42Z : No. of bitstreams: 1 000495609000001.pdf: 1583834 bytes, checksum: 8742e54105dab51e8a7995a451481fe5 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-04-20T20:23:40Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-11en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/339357-
dc.contributor.departmentDepartamento de Sistemas da Informaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordMedical imagingpt_BR
dc.subject.keywordLanczos methodpt_BR
dc.subject.keywordImage resamplingpt_BR
dc.identifier.source000495609000001pt_BR
dc.creator.orcid0000-0003-0125-630Xpt_BR
dc.type.formArtigopt_BR
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