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%.
Tóm tắt
Ung Thư Vú là loại ung thư được chẩn đoán phổ biến nhất và là nguyên nhân thứ năm gây tử vong ở phụ nữ. Việc phát hiện sớm căn bệnh này không chỉ tăng tỷ lệ sống sót mà còn giảm chi phí điều trị. Chụp nhũ ảnh là phương pháp chẩn đoán hình ảnh hiện nay để xác định và chẩn đoán sớm khối u ác tính ở vú. Trong bài báo này, chúng tôi đề xuất kỹ thuật phân loại dựa trên kiến trúc mạng NasNetLarge, MobileNetV2, InceptionV3, DenseNet121 và Vision Transformer để phân loại ảnh nhũ tuyến vú là bình thường, lành tính hoặc ác tính. Qua kết quả thực nghiệm cho thấy độ chính xác của mô hình đề xuất lên đến 99%.
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