PHÂN LOẠI UNG THƯ VÚ TRÊN ẢNH NHŨ SỬ DỤNG KỸ THUẬT HỌC SÂU VÀ MẠNG VISION TRANSFORMER

Abstract

Breast Cancer is the most commonly diagnosed cancer and the fifth leading cause of death in women. Early detection of this disease not only increases the survival rate but also reduces the cost of treatment. Mammography (X-ray mammography) is the current imaging method to identify and diagnose breast malignancies early. In this paper, we propose a classification technique based on network architecture NasNetLarge, MobileNetV2, InceptionV3, DenseNet and Vision Transformer to classify mammograms as normal, benign or malignant. Experimental results show that the accuracy of the proposed model is up to 99%.