Initial Results of Automated Melanoma Recognition

In order to test the ability to automate early skin cancer recognition, a system for the computerized analysis of images obtained from epiluminescence microscopy (ELM) has been developed. As an initial step, the boundaries of the skin lesion are determined by global thresholding and morphological operations. Then, a set of features containing information about the malignity of the lesion is extracted. This set includes both shape and radiometric features. Finally, a KarhunenLoeve -transform and a minimum distance classification are applied in order to classify the lesion as either benign or malignant. It was found that 86% of the test images were classified correctly. 1. Introduction During the last fifty years the occurrence of melanoma has dramatically increased. While in the thirties of this century one out of 100 000 people living in the United States or Europe suffered from melanoma, this number has risen to 15 out of 100 000 nowadays, with the tendency still increasing. This tre..