Quantitative features for computer-aided melanoma classification using spatial heterogeneity of eumelanin and pheomelanin concentrations

Daniel S. Cho, Shahid A. Haider, Robert Amelard, Alexander Wong, David A. Clausi

Abstract: The current computer-aided melanoma diagnostic technique employs the features that extracted from the surface level of skin, and any under-skin information is ignored. Since the colour formation of lesion is vastly influenced by the concentration of melanin, the quantitative features of spatial heterogeneity of melanin concentration was proposed. To quantify the spatial heterogeneity of eumelanin and pheomelanin concentrations, the concentration maps were divided into two and the Earth mover's distance between the concentration clusters on both sides was measured. The proposed features were evaluated on 206 dermatological images (119 melanoma cases, 87 benign cases) using a cross-validation scheme. The results show that adopting spatial heterogeneity of melanin concentrations improved the sensitivity, specificity, and accuracy of diagnosing melanoma.