A Hybrid Multistage Deep Learning System for Breast Cancer Classification
Saad Alkentar, Abdulkareem Assalem · Sylwan · 2024
Breast cancer is the second cancer-related death cause among women worldwide. Mammography is the main screening tool for breast cancer detection. Deep learning, a subset of artificial intelligence, has shown remarkable potential in medical image analysis. This particular study proposes a deep learning model to assist in the diagnosis of breast cancer. By employing unsupervised clustering algorithms to eliminate image noise and applying custom filters for image preprocessing, we achieved remarkable results in enhancing both digital and film scan images. Our proposed approach enabled the development of a robust model that surpassed the baseline model by 3%, reaching an impressive accuracy of 96.6%.