Method for determining skin lesions from images using neural network

Abstract

The paper proposes a system for determining malignant skin neoplasms. The use of convolutional neural networks for determining skin tumors from images is considered. A convolutional neural network of deep learning has been developed and modeled, which allows you to determine and classify pigmented skin lesions by examining photographs. The article proposes a system for determining malignant skin neoplasms. The proposed neural network has the basic parameters of the VGG-A architecture with a maximum number of epoch training of 10. The accuracy of the determination of the proposed model of the convolutional neural network is at least 77%. The minimum learning loss function was 0.5577. As a result of the work, a database of training photos of real pigmented skin formations taken from the international open archive ISIC Melanoma Project was used, which is a database of digital images of various types of skin lesions, was formed. Using the proposed model can be of great help in determining and diagnosing malignant skin lesions by dermatologists