Image Guided

Image-guided surgery aims to improve surgical precision and outcomes by integrating real-time imaging data with surgical procedures. Current research focuses on developing robust and accurate registration methods between pre-operative images (e.g., CT, MRI) and intraoperative data (e.g., endoscopy, ultrasound), often employing deep learning architectures like U-Nets, transformers, and YOLO for tasks such as object detection, segmentation, and pose estimation. These advancements are enabling improved visualization, navigation, and measurement capabilities during surgery, leading to potentially safer and more effective interventions across various surgical specialties.