A Portable Embedded System for Skin Lesions Detection

Abstract

Skin cancer is one of the most common types of cancer in the present decade. It can be classified into two categories: melanoma and non-melanoma. Melanoma is a dangerous, rare, and fatal type of skin cancer. Detection of melanoma in early stages is beneficial because it can improve the survival rate. As such in this paper, we developed an embedded system using a Jetson Nano that employs image processing techniques based on the ABCD rule to classify skin lesions according risk levels. The structure of the proposed system consists of two phases: the first phase involves an algorithm that performs segmentation, feature extraction, and classification; the second phase includes the electronic and mechanical design of the embedded system. This embedded system is intended to serve as a support tool for patients and doctors in the diagnosis of skin lesions and it represents the first of its kind in Bolivia.