Intraoperative Image

Intraoperative image analysis focuses on using images captured during surgery to improve surgical precision and outcomes. Current research emphasizes developing robust and efficient methods for registering preoperative and intraoperative images from various modalities (e.g., CT, X-ray, ultrasound, MRI), often employing deep learning architectures like convolutional neural networks and novel optimization algorithms to overcome challenges like image quality variations and geometric distortions. These advancements are crucial for improving surgical navigation, enabling real-time 3D reconstruction of anatomy, and facilitating automated tasks such as organ segmentation and guidewire tracking, ultimately leading to safer and more effective surgical procedures.