Convolutional Neural Network System for Melanoma Identification

Melanoma is a very dangerous type of skin cancer and its detection in the early stages is necessary for proper treatment. The article proposes an intelligent system, based on the fusion of the decisions of several neural networks to increase the performance in melanoma detection from dermatoscopic images. The system implementation method is based on the optimal choice of the number and type of neural networks involved by testing the possible combinations. According to the selection procedure, a system was implemented with four neural networks DenseNet 201, VGG 19, MobileNet, and EfficientNet. The results obtained on two different databases (ISIC 2019 - for learning, validation, and testing - and PH2 for testing) were better than those obtained on individual networks or in other works from literature.