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Detection of Tumoral Epithelial Lesions Using Hyperspectral Imaging and Deep Learning

We propose a new method for the analysis and classification of HSI images. The method uses deep learning to interpret the molecular vibrational behaviour of healthy and tumoral human epithelial tissue, based on data gathered via SWIR (short-wave infrared) spectroscopy. We analyzed samples of Melanom...

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Detalles Bibliográficos
Autores principales: de Lucena, Daniel Vitor, da Silva Soares, Anderson, Coelho, Clarimar José, Wastowski, Isabela Jubé, Filho, Arlindo Rodrigues Galvão
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304037/
http://dx.doi.org/10.1007/978-3-030-50420-5_45
Descripción
Sumario:We propose a new method for the analysis and classification of HSI images. The method uses deep learning to interpret the molecular vibrational behaviour of healthy and tumoral human epithelial tissue, based on data gathered via SWIR (short-wave infrared) spectroscopy. We analyzed samples of Melanoma, Dysplastic Nevus and healthy skin. Preliminary results show that human epithelial tissue is sensitive to SWIR to the point of making possible the differentiation between healthy and tumor tissues. We conclude that HSI-SWIR can be used to build new methods for tumor classification.