Advancements in computer-aided breast cancer diagnosis utilizing deep learning and medical imaging

Breast cancer is a prevalent malignant tumor worldwide, and early detection is essential for successful treatment and recovery. This paper examines the computer-aided detection of breast cancer using two approaches: traditional image processing and deep learning technology. It also introduces the commonly used experimental methods in breast cancer diagnosis, the performance detection indicators of the model, and the advantages and challenges of deep learning. Additionally, the article outlines the key issues in breast cancer pathological image classification and discusses the future development trend of deep learning technology for breast cancer diagnosis.