Design of a Telemedicine System for Classification of Breast Cancer Images
Thanh-Tam Nguyen, Nguyễn Thanh Hải, Tin-Trung Nguyen · Technical Education Science/Giáo dục Kỹ thuật · 2025
Breast cancer is one of complex breast lesions. Therefore, accurate diagnosis to determine whether there is cancer disease or not, to determine which stage is a challenge for most doctors. This article proposes a telemedicine system for diagnosing breast cancer disease using EfficientNet-B7 in AI model, in which three image sets of Benign, Malignant and Normal are used. The main points are that, this telemedicine system is designed and calculated suitably so that a DICOM image can be transmitted from the image collected place to a server for classification and diagnosis, in which protocols and storage parts in this system are carefully selected and tested for its efficiency. Furthermore, layers and coefficients of the EfficientNet-B7 model are calculated and selected to increase the classification performance. Thus, the overall system results produced an accuracy of about 89.58%, which is a significant result for a complex and challenging system. Thus, the system can be improved in the future by enhancing the image sets, updating the deep learning network appropriately, and configuring a powerful enough server system.