Segmentation of pigmented skin lesions using Non-negative Matrix Factorization

Melanoma is a type of malignant pigmented skin lesion, which currently is among the most dangerous existing cancers. Segmentation is an important step in computer-aided pre-screening systems for pigmented skin lesions, because a good definition of the lesion area and its rim is very important for discriminating between benign and malignant cases. In this paper, we propose to segment pigmented skin lesions using the Non-negative Matrix Factorization of the multi-channel skin lesion image representation. Our preliminary experimental results on a publicly available dataset suggest that our method obtains lower segmentation errors (in average) than comparable state-of-the-art methods proposed in literature.