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Background
Hyperspectral imaging (HSI) is an emerging modality for the gross pathology of the skin. Spectral signatures of HSI could discriminate malignant from benign tissue. Because of inherent redundancies in HSI and in order to facilitate the use of deep‐learning models, dimension reduction is a common preprocessing step. The effects of dimension reduction choice, training scope, and number of...
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