AI-Enhanced Digital Twin Augmented Reality System for Precision Cranial Trauma Reconstruction.

The process of reconstructing cranial trauma requires precise medical work because it needs multiple medical disciplines to work together while using special visual technology. The study introduces an AI-powered Digital Twin Augmented Reality system which enhances surgical planning and intraoperative support and creates personalized reconstruction results. The system creates a dynamic digital twin model of cranial structures by combining patient imaging data which includes CT and MRI scans. The system uses artificial intelligence algorithms to study anatomical differences which help determine the best reconstruction methods and create implant designs. The augmented reality component enables real-time visualization of the digital twin overlaid onto the patient’s anatomy which improves spatial understanding and surgical performance. The system uses artificial intelligence analytics together with augmented reality visualization to achieve accurate alignment while it minimizes uncertainty during surgery and protects against potential complications. Surgeons use the platform's preoperative simulation tools to practice their surgical procedures by testing various reconstruction techniques before actual surgery begins. The experimental results prove that the new method improves accuracy for defect reconstruction while reducing surgical time and enhancing decision-making processes when compared to existing methods. The system uses digital twin technology to provide continuous system updates which operate based on feedback received during surgical procedures thus creating a surgical environment that responds to changes and develops through time. The research demonstrates how artificial intelligence, digital twin modeling and augmented reality technology combine to create advancements in precision medicine for cranial trauma treatment. The system delivers an expandable and cuttingedge solution which will enhance clinical results while streamlining surgical processes and advancing the field of personalized reconstructive surgery