Advancing breast cancer screening through the integration of artificial intelligence and ultrafast MRI

This thesis is dedicated to advancing breast cancer screening and diagnosis through the development of artificial intelligence (AI) models for ultrafast breast MRI analysis. Breast cancer, a global health concern, underscores the need for early detection. While mammography is widely used, its limitations necessitate improved screening methods. Dynamic contrast-enhanced MRI, known for high sensitivity, holds promise, particularly for women with dense breasts. This thesis presents a comprehensive approach with AI models that collectively address various aspects of breast cancer screening, from identifying normal scans to locating lesions, distinguishing benign from malignant cases, and improving density assessment. These models offer the potential to enhance screening efficiency, accessibility, and personalization, ultimately improving early breast cancer detection and patient care