dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorSuzuki, Celso T. N.
dc.creatorGomes, Jancarlo F.
dc.creatorFalcao, Alexandre X.
dc.creatorShimizu, Sumie H.
dc.creatorPapa, João Paulo
dc.date2014-05-27T11:30:13Z
dc.date2016-10-25T18:52:49Z
dc.date2014-05-27T11:30:13Z
dc.date2016-10-25T18:52:49Z
dc.date2013-08-22
dc.date.accessioned2017-04-06T02:35:27Z
dc.date.available2017-04-06T02:35:27Z
dc.identifierProceedings - International Symposium on Biomedical Imaging, p. 460-463.
dc.identifier1945-7928
dc.identifier1945-8452
dc.identifierhttp://hdl.handle.net/11449/76314
dc.identifierhttp://acervodigital.unesp.br/handle/11449/76314
dc.identifier10.1109/ISBI.2013.6556511
dc.identifier2-s2.0-84881627920
dc.identifierhttp://dx.doi.org/10.1109/ISBI.2013.6556511
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/897015
dc.descriptionIntestinal parasitosis constitutes a serious health problem in most tropical countries. The diagnosis of enteroparasites in laboratory routine relies on the examination of stool samples using optical microscopy and the error rates usually range from moderate to high. Approaches based on automatic image analysis have been proposed, but the methods are usually specific for some species, some of them are computationally expensive, and image acquisition and focus are manual. We present a solution to automate the diagnosis of the 15 most common species of enteroparasites in Brazil, using a sensitive parasitological technique, a motorized microscope with digital camera for automatic image acquisition and focus, and fast image analysis methods. The results indicate that our solution is effective and suitable for laboratory routine, in which the exam must be concluded in a few minutes. © 2013 IEEE.
dc.languageeng
dc.relationProceedings - International Symposium on Biomedical Imaging
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAutomated diagnosis
dc.subjectimage segmentation
dc.subjectintestinal parasitosis
dc.subjectmicroscopy image analysis
dc.subjectpattern recognition
dc.subjectAutomatic image analysis
dc.subjectCommon species
dc.subjectImage analysis method
dc.subjectIntestinal parasites
dc.subjectMicroscopy image analysis
dc.subjectTropical countries
dc.subjectImage acquisition
dc.subjectImage analysis
dc.subjectImage segmentation
dc.subjectMedical imaging
dc.subjectOptical microscopy
dc.subjectPattern recognition
dc.subjectOptical data storage
dc.titleAutomated diagnosis of human intestinal parasites using optical microscopy images
dc.typeOtro


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