Implant Position

Implant position determination is a crucial aspect of various medical procedures, impacting surgical precision and patient outcomes. Current research focuses on automating implant placement using advanced image processing techniques and machine learning models, including deep neural networks (like transformers and U-Nets), to analyze medical images (e.g., CBCT scans, fluoroscopic images) and predict optimal implant locations. These efforts leverage techniques such as 3D contextual information processing, multi-scale feature extraction, and robust alignment algorithms to overcome challenges like anatomical variability and image noise. The development of accurate and automated implant positioning systems promises to improve surgical planning, reduce procedural errors, and enhance patient care across diverse applications, including cranioplasty, dental implantology, and knee arthroplasty.