PERFORM DIGITAL IMAGE PROCESSING ON THE FPGA AND APPLY AN ANALYSIS OF ABNORMAL AREAS OF THE SKIN TO DIAGNOSE EARLY SKIN CANCER RISK

Abstract

Detecting abnormalities on the skin, especially signs for early skin cancer, is very important. In recent years, skin cancer is considered one of the most dangerous types of cancers found in humans. Early detection of melanoma can be helpful for treatment. Medical imaging plays an important role in the early detection of abnormal skin markings based on medical images. In this paper we present a method to assist physicians in detecting skin abnormalities using visualization tools rendered on FPGAs. The input of the system is skin lesions and then by applying imaging techniques it will analyze, determine the size of abnormalities, calculate parameters and make conclusions. Early on the presence of skin cancer. The scanners image analysis tools examine different malignant melanoma parameters, such as Asymmetry, Border, Color, Diameter, (ABCD), size and shape analysis for image segments and counting phases. Features will be implemented on FPGA and System Generator (SG) tools. Parameters to be extracted are used to classify images and to predict early on the skin as normal or damaged or malignant.