A Visual Analysis of Ultrasound Breast Cancer Scans with Segmentation, Classification and Explainable AI

The amount of people who are suffering from breast cancer has increased over the years. The people affected by breast cancer have an impact on their physical and emotional health. Detecting breast cancer at an initial stage is very important to prevent the affected ones but doing it at an early stage is a hectic task for healthcare systems as they have to perform comprehensive screening, diagnosis treatment, and support services. Regular screening mammograms and clinical breast examinations improve the chance of survival. Worldwide detection of breast cancer in women remains difficult even though there are advancements in the technology of diagnosis and treatment. To tackle the issue, this study performs multiple segmentation models on Ultrasound scans that predict cancer at an initial stage. The proposed model’s workflow is segmentation models, developing the ML models, and then followed by explanation using Explainable AI libraries.