FAROOQ, SAJIDGERMANO, GLEICESTANCARI, KLEBER A.RAFFAELI, ROCIOCROCE, MARIA V.CROCE, ADELA E.ZEZELL, DENISE M.2024-02-082024-02-08FAROOQ, 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>. DisponÃvel em: http://repositorio.ipen.br/handle/123456789/34587.http://repositorio.ipen.br/handle/123456789/34587Here, 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).openAccessspectrafourier transformationinfrared spectraepitheliomasskinneoplasmsdiagnostic techniquesmachine learningA 3D discriminant analysis for hyperspectral FTIR imagesTexto completo de evento10.1109/OMN/SBFOTONIOPC58971.2023.102309330000-0001-7404-9606https://orcid.org/0000-0001-7404-9606