Analysis of the Influence of Color Normalization in the Classification of Non-Hodgkin Lymphoma Images

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dc.contributor.authorGoncalves Ribeiro, Matheus [UNESP]
dc.contributor.authorAlves Neves, Leandro [UNESP]
dc.contributor.authorFreire Roberto, Guilherme
dc.contributor.authorTosta, Thaina A. A.
dc.contributor.authorMartins, Alessandro S.
dc.contributor.authorDo Nascimento, Marcelo Z.
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal de Uberlândia (UFU)
dc.contributor.institutionFederal University of ABC
dc.contributor.institutionFederal Institute of Triângulo Mineiro (IFTM)
dc.date.accessioned2019-10-06T16:19:15Z
dc.date.available2019-10-06T16:19:15Z
dc.date.issued2019-01-15
dc.description.abstractIn this work, a method is proposed to analyze the influence of color normalization in the classification lymphoma images. The approach combines multidimensional fractal techniques, curvelet transforms and Haralick features. The method considered a feature selection technique and different classification approaches to evaluate the combinations, such as decision tree, random forest, support vector machine, naive bayes and k-star. The classifications were analyzed considering three common lymphoma classes: mantle cell lymphoma, follicular lymphoma and chronic lymphocytic leukemia. The best result was achieved for the extraction from input images, features obtained mostly from lacunarity and percolation from curvelet sub-images, using random forest classifier. The tests were considered with 10-fold cross-validation and the result was a rate of AUC=0.963. The color normalization was not able to provide relevant classification rates. The obtained performance with the analysis over different types of features, classifiers and color normalization influence are important contributions to the identification of the lymphoma cancer.en
dc.description.affiliationDepartment of Computer Science and Statistics (DCCE) São Paulo State University (UNESP)
dc.description.affiliationFaculty of Computation (FACOM) Federal University of Uberlândia (UFU)
dc.description.affiliationCenter of Mathematics Computing and Cognition Federal University of ABC
dc.description.affiliationFederal Institute of Triângulo Mineiro (IFTM)
dc.description.affiliationUnespDepartment of Computer Science and Statistics (DCCE) São Paulo State University (UNESP)
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)
dc.description.sponsorshipIdCAPES: 1646248
dc.description.sponsorshipIdCNPq: 427114/20160
dc.description.sponsorshipIdFAPEMIG: TEC - APQ-02885-15
dc.format.extent369-376
dc.identifierhttp://dx.doi.org/10.1109/SIBGRAPI.2018.00054
dc.identifier.citationProceedings - 31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018, p. 369-376.
dc.identifier.doi10.1109/SIBGRAPI.2018.00054
dc.identifier.scopus2-s2.0-85062237452
dc.identifier.urihttp://hdl.handle.net/11449/188789
dc.language.isoeng
dc.relation.ispartofProceedings - 31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectAnalysis of the Influence
dc.subjectclassification
dc.subjectcolor normalization
dc.subjectnon Hodgkin Lymphoma
dc.titleAnalysis of the Influence of Color Normalization in the Classification of Non-Hodgkin Lymphoma Imagesen
dc.typeTrabalho apresentado em evento

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Artigos - Ciência da Computação e Estatística - IBILCE