Prof. Xiaojun Chen
Project Description and Objectives:
As a modern minimally-invasive surgery, microscopic/endoscopic techniques are widely used in the field of surgery, however, the current orthopedic robots are only applicable for traditional open surgery. Their working principles, operation modes, as well as the software and hardware systems simply do not apply to microscopic/endoscopic surgeries as they are currently. In this project, some leading-edge algorithms based on artificial intelligence regarding multi-modal image registration, automatic segmentation, high quality visualization, and precise planning are proposed for important anatomical structures in the musculoskeletal system. Then, a surgical navigation system based on Augmented Reality is established based on real time segmentation, non-rigid registration, and 3D reconstruction for an intra-operative ultrasound and endoscopic images, aiming at solving the problems of soft tissue deformation and tracking. Finally, the comprehensive, light, and smart mechanical structures and control systems for surgical robots in endoscopic orthopedics are designed and integrated with our previously self-developed surgical navigation and robotic system, achieving the ultimate prototype of “Microscopic/Endoscopic Surgical Robotics Based on Augmented Reality”. The accuracy, effectiveness, and reliability of the whole system will be validated through phantom experiments and clinical trials, for the goal of the mass clinical application. The research outcome of this project will promote the personalization, safety, accuracy, and minimal invasion of microscopic/endoscopic orthopedics, leading the direction in the international field of orthopedic robotics.
The interested student should be very proficient in C++ programming and have a basic knowledge of medical image processing.