Rapidly calculating blood flow fields from medical imaging data (CT/Ultrasound) in the coronary arteries is critical for accurate diagnosis and effective treatment planning. This project aims to leverage Physics-Informed Neural Networks (PINNs) to achieve this goal efficiently and accurately.