Enhancing Breast Cancer Detection with AI: Ensuring Image Security and Diagnostic Precision Through Deep Learning Techniques
Thrushna Matharasi, Priyam Ganguly, Isha Mukherjee, Sanjeev Lakkaraju · 2025
This study aims to explore and evaluate the effectiveness of Artificial Intelligence (AI), particularly Deep Learning (DL), as an innovative tool in the fight against breast cancer. As breast cancer remains one of the leading causes of mortality among women, numerous solutions have been proposed to address this pressing issue. AI, however, has emerged as a pivotal support system for radiologists, enhancing diagnostic accuracy and efficiency. Therefore, the study focuses on two key approaches i.e. image classification and pixel segmentation. While image classification provides valuable insights, it faces certain limitations, prompting the adoption of pixel segmentation as a more advanced method. Pixel segmentation offers detailed, essential information that, when combined with the expertise of medical professionals, has the potential to significantly enhance early detection and prevention strategies. By leveraging the synergy between AI and expert analysis, this approach represents a promising advancement in improving breast cancer diagnostics and patient outcomes.