Presenting KIDS: Knee Injury Detection System, our Techgium 2024 finalist project revolutionizing knee pathology diagnosis using advanced AI. MRI scans present a unique challenge due to the intricate nature of knee structures. Our solution addresses this by employing a specialized YOLOv8 model, renowned for its efficiency in real-time object detection.

Our system goes beyond mere detection; it identifies and grades specific knee issues such as meniscal tears, arthritis, and ACL injuries with unparalleled accuracy. Built on the robust YOLOv8 architecture, our model extracts intricate spatial patterns from three-dimensional knee MRI data, ensuring comprehensive pathology coverage.

But we didn't stop there. KIDS features an intuitive application interface, allowing seamless interaction for both patients and doctors. Doctors can efficiently manage cases, accessing patient details, scans, and reports through a user-friendly interface.

Checkout the demo: KIDS (Knee injury detection system) https://youtu.be/MlJ82OuA4V8