This paper deals with ELM image processing for automatic analysis of pigmented skin lesions which represents one of the greatest challenges of dermatologic practice today. The “ELM 7 point checklist” defines a set of seven features, based on colour and texture parameters, which describe the malignancy of a lesion. It has been revealed as faster and with the same accuracy than the traditional ABCD criteria in the diagnosis of melanoma. A preliminary approach to the automated diagnosis of melanocytic skin lesions, based on ELM 7 point checklist is proposed. In particular, the image processing algorithms and classification techniques involved in the automatic detection of the occurrence of two criteria (Blue-whitish Veil and Regression structures) are introduced and the experimental results are reported.
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Leo et al. (2009) studied this question.
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