Cutaneous melanoma risk evaluation through digital image processing

Melanoma is the most aggressive type of human cancer but also the most likely to be cured if detected in its early stages. The risk of skin lesions to turn into melanoma can be easily evaluated by dermatologists using a non-invasive procedure called dermoscopy. This paper addresses the issue of melanoma risk evaluation through digital processing of macroscopic skin lesions images. The main goal of our research is the development of an application for tracking the time evolution of skin lesions and evaluating the risk of these lesions to turn into melanoma. The first step in the evaluation process is the extraction of the pigmented skin lesions by means of image segmentation. The two objectives presented in this paper are the determination of the best suited segmentation method in terms of computational complexity and the evaluation of the color space used for digital image representation in order to obtain good initial segmentation results.