Mobile melanoma detection application for Android smart phones

Abstract

Current attempts of melanoma detection using Support Vector Machines (SVMs) have proven to be quite efficient; some approaches “use texture information ONLY to classify the benign and malignancy of a tumor” and still have achieved average accuracy of classification up to 70% [1]. Very recently, these decision making algorithms have been adapted for use in the mobile world as smart-phone applications. The goal of our research was to create a mobile melanoma detection application which could be used for the identification of melanoma on the skin in its earliest stages. This ‘app’ would be run on smartphone devices with cameras which could take a picture of a particular skin abnormality. The image of the lesion would be sent from the smart-phone to a central server/computer which would use color and symmetry based analysis with a Support Vector Machine (SVM) to classify the image as benign or malignant. The results would be sent back to the user, and assist in expediting the process of determining when to seek professional services.