Skip to content
DSML.KZ
Publications

Talk · Mediterranean Conference on Embedded Computing · June 1, 2020

Method for Determining Skin Lesions from Images Using Neural Network

Ulyana Alekseevna Lyakhova, Pavel Alekseyevich Lyakhov, Nikolay Ivanovich Chervyakov, Dmitrii Kaplun, Alexander S. Voznesensky

Dmitry Kaplun
Open via DOI

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.

Cutaneous Melanoma Detection and ManagementAI in cancer detectionAdvanced Neural Network Applicationsskin lesion classificationpigmented skin lesionsmelanoma detection

More by Dmitry Kaplun