Supplemental melanoma diagnosis for darker skin complexion gradients

Abstract

Melanoma represents one of most malignant tumors associated with melanocytes in pigmented cells of the skin and in particular is a result of malignant transformation of melanocytes. Due to migration of neural cell crest, melanoma can develop not only on skin, but on oral and genital mucosa, and also gastrointestinal tract and brain. Melanoma is usually present and manifests itself with changes in color, size, contour and configuration, or may occur as new pigmented lesions. In particular, melanoma represents the sixth leading cause of malignancy in the United States with much higher mortality rate among non-Caucasian population, although is more common among whites. Considering its complexity, clinical diagnosis of melanoma is challenging even for experienced dermatologists. This is why it is necessary to develop computer assisted diagnostic tool for melanoma detection focused on dark and fair complexion skin which adds more objective judgments based on quantitative measures. Therefore, specialized algorithms were developed and tested utilizing databases including images of a variety of skin cancer manifestations. Those diagnostic indicators were assessed utilizing commonly used ABCDE criteria for different skin complexions and also natural and simulated darker background reflecting darker skin tones associated with different ethnic groups. Incorporated Canny, Prewitt, Roberts and Sobel edge detectors allowed to optimize melanoma diagnosis for darker skin tones and assess the degree of correct classification for each of ABCDE criterion reflecting varied skin complexion.