Texture Characterization Fuzzy Logic-Based Model for Melanoma Diagnosis

Abstract

Over the past two decades, the world has known a significant number of deaths from cancer. More specifically, melanoma which is considered the deadliest form of skin cancer causes a remarkable percentage of all cancer deaths. Therefore, the health and disease management community has exceedingly invested in creating efficient devices that help dermatologists to early evaluate and inspect a specific kind of skin disease. These systems use some measurable visual component describing the shape, color, and texture of skin diseases to recognize them and to specify their malignancy. In this article, a fuzzy logic-based model is introduced which characterizes statistical texture features. The fuzzy model is built to classify skin lesions into malignant and benign based on the characterization of statistical texture features. This method has been proven to yield reliable results compared to the machine learning-based model. Besides, it is more stable and unbiased in classifying skin lesions than machine learning models.