Using computational learning for non-melanoma skin cancer and actinic keratosis near-infrared hyperspectral signature classification.

We have shown that the Near-Infrared region of the electromagnetic spectrum is highly useful for the identification and study of non-melanoma type skin lesions. While the results are promising, further research is required to develop more robust algorithms that can minimize the impact of noise in these datasets before clinical application is feasible.