Published Paper Details:

Breast cancer is one of the leading causes of cancer related deaths among women worldwide. Early detection and accurate diagnosis of breast cancer can significantly improve the chances of successful treatment and long-term survival. Mammography is a widely used imaging technique for breast cancer screening and diagnosis. In recent years, there has been growing interest in developing computer-aided detection (CAD) systems to improve the accuracy and efficiency of mammography interpretation. This paper presents an overview of the current state-of-the-art in breast cancer detection using mammography and CAD systems. The paper discusses the challenges and opportunities in developing CAD systems, including image preprocessing, feature extraction, classification, and validation. Finally, the paper highlights some of the recent advances in deep learning-based CAD systems and their potential impact on breast cancer detection and diagnosis.