A 3D discriminant analysis for hyperspectral FTIR images

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dc.contributor.authorFAROOQ, SAJIDpt_BR
dc.contributor.authorGERMANO, GLEICEpt_BR
dc.contributor.authorSTANCARI, KLEBER A.pt_BR
dc.contributor.authorRAFFAELI, ROCIOpt_BR
dc.contributor.authorCROCE, MARIA V.pt_BR
dc.contributor.authorCROCE, ADELA E.pt_BR
dc.contributor.authorZEZELL, DENISE M.pt_BR
dc.coverageInternacionalpt_BR
dc.creator.eventoINTERNATIONAL CONFERENCE ON OPTICAL MEMS AND NANOPHOTONICS; SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCEpt_BR
dc.date.accessioned2024-02-08T15:32:13Z
dc.date.available2024-02-08T15:32:13Z
dc.date.eventoJuly 31 - August 3, 2023pt_BR
dc.description.abstractHere, we apply a 3D discriminant analysis approach to analyze FTIR hyperspectral images of normal vs malignant Melanoma (MM) samples for skin cancer diagnosis. For this porpose we used 2 samples, for Normal (49k) and for MM(90k). Our results evidence the outstanding performance with accuracy up to 81% for big data (> 100k).pt_BR
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)pt_BR
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.description.sponsorshipIDCNPq: INCT-INTERAS 406761/2022-1; INCT-INFO 465763/2014-6; Sisfoton 440228/2021-2; PQ 314517/2021-9pt_BR
dc.description.sponsorshipIDCAPES: 001pt_BR
dc.description.sponsorshipIDFAPESP: 17/50332-0; 21/00633-0pt_BR
dc.event.siglaOMN; SBFoton IOPCpt_BR
dc.identifier.citationFAROOQ, SAJID; GERMANO, GLEICE; STANCARI, KLEBER A.; RAFFAELI, ROCIO; CROCE, MARIA V.; CROCE, ADELA E.; ZEZELL, DENISE M. A 3D discriminant analysis for hyperspectral FTIR images. In: INTERNATIONAL CONFERENCE ON OPTICAL MEMS AND NANOPHOTONICS; SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE, July 31 - August 3, 2023, Campinas, SP. <b>Proceedings...</b> Piscataway, NJ, USA: IEEE, 2023. DOI: <a href="https://dx.doi.org/10.1109/OMN/SBFOTONIOPC58971.2023.10230933">10.1109/OMN/SBFOTONIOPC58971.2023.10230933</a>. Disponível em: http://repositorio.ipen.br/handle/123456789/34587.
dc.identifier.doi10.1109/OMN/SBFOTONIOPC58971.2023.10230933pt_BR
dc.identifier.orcid0000-0001-7404-9606pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-7404-9606
dc.identifier.urihttp://repositorio.ipen.br/handle/123456789/34587
dc.localPiscataway, NJ, USApt_BR
dc.local.eventoCampinas, SPpt_BR
dc.publisherIEEEpt_BR
dc.rightsopenAccesspt_BR
dc.subjectspectra
dc.subjectfourier transformation
dc.subjectinfrared spectra
dc.subjectepitheliomas
dc.subjectskin
dc.subjectneoplasms
dc.subjectdiagnostic techniques
dc.subjectmachine learning
dc.titleA 3D discriminant analysis for hyperspectral FTIR imagespt_BR
dc.typeTexto completo de eventopt_BR
dspace.entity.typePublication
ipen.autorSAJID FAROOQ
ipen.autorKLEBER ADRIANI STANCARI
ipen.autorDENISE MARIA ZEZELL
ipen.autorGLEICE CONCEICAO MENDONCA GERMANO
ipen.codigoautor15722
ipen.codigoautor15402
ipen.codigoautor693
ipen.codigoautor15828
ipen.contributor.ipenauthorSAJID FAROOQ
ipen.contributor.ipenauthorKLEBER ADRIANI STANCARI
ipen.contributor.ipenauthorDENISE MARIA ZEZELL
ipen.contributor.ipenauthorGLEICE CONCEICAO MENDONCA GERMANO
ipen.date.recebimento24-02
ipen.event.datapadronizada2023pt_BR
ipen.identifier.ipendoc30192pt_BR
ipen.identifier.ods3
ipen.notas.internasProceedingspt_BR
ipen.type.genreArtigo
relation.isAuthorOfPublication60d3fba4-40e1-482c-9eda-4530bc63fecb
relation.isAuthorOfPublication98ed2954-eea9-494d-a2a1-92deb707a41c
relation.isAuthorOfPublicationa565f8ad-3432-4891-98c0-a587f497db21
relation.isAuthorOfPublicatione2b5b321-8d39-414f-b042-f47726b2c5a3
relation.isAuthorOfPublication.latestForDiscovery60d3fba4-40e1-482c-9eda-4530bc63fecb
sigepi.autor.atividadeZEZELL, DENISE M.:693:920:Npt_BR
sigepi.autor.atividadeSTANCARI, KLEBER A.:15402:920:Npt_BR
sigepi.autor.atividadeGERMANO, GLEICE:15828:920:Npt_BR
sigepi.autor.atividadeFAROOQ, SAJID:15722:920:Spt_BR
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