Doutorado em Ciência da Computação em Rede - UFMS/UFG (INF)
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Item Classificação de tecidos epiteliais tumorais empregando imagens hiperespectrais e infravermelho de ondas curtas(Universidade Federal de Goiás, 2021-08-04) Lucena, Daniel Vitor de; Coelho, Clarimar José; http://lattes.cnpq.br/1350166605717268; Soares, Anderson da Silva; http://lattes.cnpq.br/1096941114079527; Soares, Anderson da Silva; Coelho, Clarimar José; Wastowski, Isabela Jubé; Laureano, Gustavo Teodoro; Soares, Fabrízzio Alphonsus Alves de Melo NunesHyperspectral Imaging (HSI) is a new concept of disease diagnosis by image analysis. Although there are many approaches for HSI image analysis, the classification of spatial informations to tumor classification is still limited. In this thesis is proposed the building of a new method of analysis and classification of present objects in HSI based on techniques of machine learning to understand the molecular vibrational behavior of healthy and tumoral human epithelial tissue by means of short-wave infrared (SWIR) spectroscopy. In the experimental study is analyzed samples of Melanoma, Dysplastic Nevus and healthy skin. Results show that human epithelial tissue is sensitive to SWIR to the point of making possible the differentiation between healthy and tumor tissues. It can be concluded that HSI-SWIR can be used to build new methods for tumor classification.