Skin Lesion Primary Morphology Classification With End-To-End Deep Learning Network

Abstract

Automatic diagnostics of skin lesions is an area of high interest. Identification of primary morphology in skin lesions could be a first step of an automatic diagnostics tool. We propose an end-to-end deep learning solution to the problem of classifying primary morphology images of types macule, nodule, papule and plaque. Experimental results show 0.775 accuracy on 4 classes and 0.8167 accuracy on 3 classes.