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dc.contributor.authorSuzuki, Celso T. N.-
dc.contributor.authorGomes, Jancarlo F.-
dc.contributor.authorFalcão, Alexandre X.-
dc.contributor.authorPapa, João Paulo-
dc.contributor.authorHoshino-Shimizu, Sumie-
dc.identifier.citationIEEE Transactions on Biomedical Engineering, v. 60, n. 3, p. 803-812, 2013.-
dc.description.abstractHuman intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.en
dc.subjectImage foresting transform (IFT)-
dc.subjectImage segmentation-
dc.subjectIntestinal parasitosis-
dc.subjectMicroscopy image analysis-
dc.subjectOptimumpath forest (OPF) classifier-
dc.subjectPattern recognition-
dc.titleAutomatic segmentation and classification of human intestinal parasites from microscopy imagesen
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.description.affiliationInstitute of Computing University of Campinas, São Paulo 13084-971-
dc.description.affiliationDepartment of Computer Science Universidade Estadual Paulista, Bauru, São Paulo 05508-900-
dc.description.affiliationFaculty of Pharmaceutical Science University of São Paulo, São Paulo 66318-
dc.description.affiliationUnespDepartment of Computer Science Universidade Estadual Paulista, Bauru, São Paulo 05508-900-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofIEEE Transactions on Biomedical Engineering-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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