Independent Component Analysis as an Effective Tool for Automated Diagnosis of Melanoma

During the last years, many diagnostic methods have been proposed aiming at early detection of malignant melanoma tumor which is among the most frequent types of skin cancer. In this paper we discuss a new approach based on independent component analysis (ICA) for classification of pigmented skin lesions in dermatological images. Features that describe the structure of lesions, and show high discriminative characteristics are extracted using ICA, and then these features along with the color features of the lesions are used to construct a classification module based on support vector machines (SVM) for the recognition of malignant melanoma versus benign nevus.