Fusion of Visual and Anamnestic Data for the Classification of Skin Lesions with Deep Learning

Abstract

Early diagnosis of skin lesions is essential for the positive outcome of the disease, which can only be resolved with surgical treatment. In this manuscript, a deep learning method is proposed for the classification of cutaneous lesions based on their visual appearance and on the patient’s anamnestic data. These include age and gender of the patient and position of the lesion. The classifier discriminates between benign and malignant lesions, mimicking a typical procedure in dermatological diagnostics. Good preliminary results on the ISIC Dataset demonstrate the importance of the information fusion process, which significantly improves the classification accuracy.