Multiscale Fractal Descriptors and Polynomial Classifier for Partial Pixels Identification in Regions of Interest of Mammographic Images

dc.contributor.authorMartins, A. S.
dc.contributor.authorNeves, L. A. [UNESP]
dc.contributor.authorNascimento, M. Z.
dc.contributor.authorGodoy, M. F.
dc.contributor.authorFlores, E. L.
dc.contributor.authorCarrijo, G. A.
dc.contributor.institutionUniversidade Federal de Uberlândia (UFU)
dc.contributor.institutionIFTM
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal do ABC (UFABC)
dc.contributor.institutionFaculdade de Medicina de São José do Rio Preto (FAMERP)
dc.date.accessioned2014-05-20T14:01:45Z
dc.date.available2014-05-20T14:01:45Z
dc.date.issued2012-06-01
dc.description.abstractComputer systems are used to support breast cancer diagnosis, with decisions taken from measurements carried out in regions of interest (ROIs). We show that support decisions obtained from square or rectangular ROIs can to include background regions with different behavior of healthy or diseased tissues. In this study, the background regions were identified as Partial Pixels (PP), obtained with a multilevel method of segmentation based on maximum entropy. The behaviors of healthy, diseased and partial tissues were quantified by fractal dimension and multiscale lacunarity, calculated through signatures of textures. The separability of groups was achieved using a polynomial classifier. The polynomials have powerful approximation properties as classifiers to treat characteristics linearly separable or not. This proposed method allowed quantifying the ROIs investigated and demonstrated that different behaviors are obtained, with distinctions of 90% for images obtained in the Cranio-caudal (CC) and Mediolateral Oblique (MLO) views.en
dc.description.affiliationUniversidade Federal de Uberlândia (UFU), Uberlandia, MG, Brazil
dc.description.affiliationIFTM, Ituiutaba, MG, Brazil
dc.description.affiliationUniv Estadual Paulista UNESP, DCCE, São Paulo, Brazil
dc.description.affiliationUFABC, Ctr Matemat Comp & Cognicao, São Paulo, Brazil
dc.description.affiliationFaculdade de Medicina de São José do Rio Preto (FAMERP) FAMERP, Dept Cardiol & Cirurgia Cardiovasc, São Paulo, Brazil
dc.description.affiliationUnespUniv Estadual Paulista UNESP, DCCE, São Paulo, Brazil
dc.format.extent1999-2005
dc.identifierhttp://dx.doi.org/10.1109/TLA.2012.6272486
dc.identifier.citationIEEE Latin America Transactions. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc, v. 10, n. 4, p. 1999-2005, 2012.
dc.identifier.doi10.1109/TLA.2012.6272486
dc.identifier.issn1548-0992
dc.identifier.lattes2139053814879312
dc.identifier.lattes7939791175456786
dc.identifier.orcid0000-0001-7385-6705
dc.identifier.urihttp://hdl.handle.net/11449/21795
dc.identifier.wosWOS:000311854600021
dc.language.isopor
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofIEEE Latin America Transactions
dc.relation.ispartofjcr0.502
dc.relation.ispartofsjr0,253
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectMammographyen
dc.subjectRegions of Interesten
dc.subjectPartial Pixelsen
dc.subjectFractal Descriptorsen
dc.subjectPolynomial Classifieren
dc.titleMultiscale Fractal Descriptors and Polynomial Classifier for Partial Pixels Identification in Regions of Interest of Mammographic Imagesen
dc.typeArtigo
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIEEE-Inst Electrical Electronics Engineers Inc
unesp.author.lattes2139053814879312
unesp.author.lattes7939791175456786[5]
unesp.author.orcid0000-0001-7385-6705[5]
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

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