Visualization of Breast Cancer and Safety: Review

Breast cancer remains a leading cause of mortality among women globally, with early detection playing a pivotal role in improving patient outcomes. The treatment and prognosis have improved significantly due to early detection. The rapid development of various imaging techniques has led to success in early detection. In this article, we will discuss the current options for breast cancer screening, including mammography (both film-screen and digital), breast magnetic resonance imaging, automated breast ultrasound, and other techniques such as digital breast tomography and breast computed tomography. In addition, we summarize the characteristic features of the modalities in a tabular view for better representation and comparability. The goal of this review is to highlight the progress made in breast cancer screening and its impact on survival rates. The review concludes that the progress in the screening techniques results in a much higher survival rate, in particular due to detections of earlier stages of tumors. In recent years, artificial intelligence has emerged as a powerful tool in the field of breast cancer management, revolutionizing detection, diagnosis, and treatment planning. The rapid growth in artificial intelligence technologies, particularly machine learning and deep learning, has enabled sophisticated analysis of imaging data, pathology, and clinical variables, significantly enhancing precision and efficiency. We highlight advancements in artificial intelligence for breast cancer in past five years, and discusses the challenges and future opportunities in integrating artificial intelligence into clinical workflows.