Preoperative 3D

Preoperative 3D modeling integrates pre-operative imaging data (CT, MRI) to create three-dimensional anatomical models for surgical planning and guidance. Current research focuses on improving the accuracy and speed of registering these models to the intraoperative reality, often employing deep learning methods (e.g., convolutional neural networks, graph convolutional networks) and differentiable rendering techniques to handle challenges like sparse data, organ deformation, and real-time constraints. This work aims to enhance surgical precision, reduce invasiveness, and improve patient outcomes across various surgical specialties, including orthopedics, neurosurgery, and laparoscopic procedures. The development of robust and efficient registration algorithms is a key area of ongoing investigation.