A developed system for melanoma diagnosis

Abstract

In recent years, there has been a fairly rapid increase in the number of melanoma skin cancer patients. Melanoma, this deadliest form of skin cancer, must be diagnosed early for effective treatment. So, it is necessary to develop a computer-aided diagnostic system to facilitate its early detection. In this paper, the proposed work is based on a combination of a segmentation method and an analytical method and aims to improve these two methods in order to develop an interface that can assist dermatologists in the diagnostic phase. As a first step, a sequence of preprocessing is implemented to remove noise and unwanted structures from the image. Then, an automatic segmentation approach locates the skin lesion. The next step is feature extraction followed by the ABCD rule to make the diagnosis through the calculation of the TDV score. In this research, three diagnosis are used which are melanoma, suspicious, and benign skin lesion. The experiment uses 40 images containing suspicious melanoma skin cancer. Based on the experiment, the accuracy of the system is 92% which reflects its viability.