Robust Automatic Detection of Hip Prostheses in X-Ray Images: A Method Based on Edge Detection and Circle Fitting

Accurate identification of hip prostheses in X-ray images are essential for effective diagnosis and treatment planning. Misidentification or delays in recognizing the implant type can complicate patient care and impact surgical outcomes. This study proposes a novel approach for the automatic detection of hip prostheses in X-ray images using deep learning techniques. By leveraging advancements in machine learning and image processing, the research aims to develop an automated system capable of accurately identifying hip implants, thereby enhancing clinical workflows and improving patient outcomes.