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.
CITATION STYLE
de Lucena, D. V., da Silva Soares, A., Coelho, C. J., Wastowski, I. J., & Filho, A. R. G. (2020). Detection of tumoral epithelial lesions using hyperspectral imaging and deep learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12139 LNCS, pp. 599–612). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-50420-5_45
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