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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/50652
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dc.creatorLuana Aparecida dos Reispt_BR
dc.creatorAna Paula Vargas Garciapt_BR
dc.creatorEgleidson Frederik do Amaral Gomespt_BR
dc.creatorFrancis G. J. Longfordpt_BR
dc.creatorJeremy Graham Freypt_BR
dc.creatorGeovanni Dantas Cassalipt_BR
dc.creatorAna Maria de Paulapt_BR
dc.date.accessioned2023-03-03T18:58:20Z-
dc.date.available2023-03-03T18:58:20Z-
dc.date.issued2020-
dc.citation.volume11pt_BR
dc.citation.issue11pt_BR
dc.citation.spage6413pt_BR
dc.citation.epage6427pt_BR
dc.identifier.doihttps://doi.org/10.1364/BOE.400871pt_BR
dc.identifier.issn2156-7085pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/50652-
dc.description.resumoWe present nonlinear microscopy imaging results and analysis from canine mammary cancer biopsies. Second harmonic generation imaging allows information of the collagen structure in the extracellular matrix that together with the fluorescence of the cell regions of the biopsies form a base for comprehensive image analysis. We demonstrate an automated image analysis method to classify the histological type of canine mammary cancer using a range of parameters extracted from the images. The software developed for image processing and analysis allows for the extraction of the collagen fibre network and the cell regions of the images. Thus, the tissue properties are obtained after the segmentation of the image and the metrics are measured specifically for the collagen and the cell regions. A linear discriminant analysis including all the extracted metrics allowed to clearly separate between the healthy and cancerous tissue with a 91%-accuracy. Also, a 61%-accuracy was achieved for a comparison of healthy and three histological cancer subtypes studied.pt_BR
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológicopt_BR
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Geraispt_BR
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.description.sponsorshipINCT – Instituto nacional de ciência e tecnologia (Antigo Instituto do Milênio)pt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICX - DEPARTAMENTO DE FÍSICApt_BR
dc.publisher.initialsUFMGpt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectMicroscopypt_BR
dc.subjectMultiphotonpt_BR
dc.subjectCancerpt_BR
dc.subjectSHGpt_BR
dc.subjectNonlinear opticspt_BR
dc.subject.otherMicroscopiapt_BR
dc.subject.otherCâncerpt_BR
dc.subject.otherÓptica não-linearpt_BR
dc.titleCanine mammary cancer diagnosis from quantitative properties of nonlinear optical imagespt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://opg.optica.org/boe/fulltext.cfm?uri=boe-11-11-6413&id=441702pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-0898-6295pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-0842-4302pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-5650-6743pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-8551-5948pt_BR
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