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Grinding trajectory generator in robot-assisted laminectomy surgery.
Qian Li1, Zhijiang Du1, Hongjian Yu2
1State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China.
International Journal of Computer Assisted Radiology and Surgery
|January 28, 2021
Summary
This study introduces an automated system for robot-assisted laminectomy surgery. It precisely plans grinding trajectories from CT scans, simplifying surgical procedures and saving valuable surgeon time.
Area of Science:
- Neurosurgery
- Robotics
- Medical Imaging
Background:
- Robot-assisted laminectomy requires complex trajectory planning.
- Manual planning is time-consuming and cumbersome for surgeons.
Purpose of the Study:
- To automate surgical target area extraction from CT images.
- To develop a method for generating robotic grinding trajectories based on CT data.
Main Methods:
- A deep neural network was developed for laminae positioning.
- Trajectory generation and grinding speed adjustment strategies were implemented.
- Algorithms process CT images to plan grinding trajectories.
Main Results:
- The laminae positioning network achieved 95.7% accuracy with 1.12 mm error.
- Simulated surgical planning met expectations on a public dataset.
- Speed adjustment algorithm resulted in smoother grinding force.
Conclusions:
- Automated extraction of laminar centers from CT images enables precise surgical trajectory planning.
- The developed system simplifies surgical planning and reduces operative time.
- This approach streamlines a traditionally cumbersome surgical task.
