Zaopeng He ^1,2 Guanghua Xu ^2,3* Guodong Zhang ^4* Zeyu Wang ⁵ Jingsong Sun ^2* Wei Li ^2* Dongbo Liu ^2* Yibin Tian ^6* Wenhua Huang ^1,7* Daozhang Cai ^1,8*

• ¹ The Third Affiliated Hospital and Third School of Clinical Medicine, Southern Medical University, Guangzhou 510630, China, Guangzhou, China
• ² Lecong Hospital of Shunde, Foshan 528315, China, Foshan, Guangdong Province, China
• ³ Guangdong Engineering Research Center for Translation of Medical 3D Printing Application, Guangdong Provincial Key Laboratory of Medical Biomechanics, National Key Discipline of Human Anatomy and School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China, Southern Medical University, Guangzhou, China
• ⁴ Department of Orthopedics, Affiliated Hospital of Putian University, Putian, Fujian Province, China
• ⁵ school of Basic Medical Sciences, Yanbian University, Yanbian 133002, China, yanbian, China
• ⁶ College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China
• ⁷ Guangdong Engineering Research Center for Translation of Medical 3D Printing Application, National Key Discipline of Human Anatomy and School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
• ⁸ Orthopedic Hospital of Guangdong Province, Academy of Orthopedics Guangdong Province，Guangzhou 510515, China, Guangzhou, China

Image-guided surgical navigation systems are widely regarded as the benchmark for computer-assisted surgical robotic platforms, yet a persistent challenge remains in addressing intraoperative image drift and mismatch. It can significantly impact the accuracy and precision of surgical procedures. Therefore, further research and development are necessary to mitigate this issue and enhance the overall performance of these advanced surgical platforms.The primary objective is to improve the precision of image guided puncture navigation systems by developing a computed tomography (CT) and structured light imaging (SLI) based navigation system. Furthermore, we also aim to quantifying and visualize intraoperative image drift and mismatch in real time and provide feedback to surgeons, ensuring that surgical procedures are executed with accuracy and reliability.A CT-SLI guided orthopedic navigation puncture system was developed. Polymer bandages are employed to pressurize, plasticize, immobilize and toughen the surface of a specimen for surgical operations. Preoperative CT images of the specimen are acquired, a 3D navigation map is reconstructed and a puncture path planned accordingly. During surgery, an SLI module captures and reconstructs the 3D surfaces of both the specimen and a guiding tube for the puncture needle. The SLI reconstructed 3D surface of the specimen is matched to the CT navigation map via two-step point cloud registrations, while the SLI reconstructed 3D surface of the guiding tube is fitted by a cylindrical model, which is in turn aligned with the planned puncture path. The proposed system has been tested and evaluated using 20 formalin-soaked lower limb cadaver specimens preserved at a local hospital.The proposed method achieved image registration RMS errors of 0.576±0.146mm and 0.407±0.234mm between preoperative CT and intraoperative SLI surface models and between preoperative and postoperative CT surface models.In addition, preoperative and postoperative specimen surface and skeletal drifts were 0.033±0.272mm and 0.235±0.197mm respectively.The results indicate that the proposed method is effective in reducing intraoperative image drift and mismatch. The 2 system also visualizes intraoperative image drift and mismatch, and provides real time visual feedback to surgeons