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Path Planning for Semi-automated Simulated Robotic Neurosurgery
Danying Hu1, Yuanzheng Gong2, Blake Hannaford1
1Biorobotics Laboratory, Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA.
Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems
|December 26, 2015
Summary
This study introduces automated robotic surgery path planning for brain tumor removal, simplifying a complex manual task for surgeons. The developed methods enable precise ablation of tumor residues using point-cloud data for improved surgical outcomes.
Area of Science:
- Neurosurgery
- Robotics
- Medical Engineering
Background:
- Manual resection of brain tumor margins is a complex and time-intensive surgical procedure.
- Current methods for robotic tumor ablation often rely on analytical geometry, limiting flexibility for irregular tumor shapes.
Purpose of the Study:
- To develop robust path planning methods for semi-automated robotic ablation of brain tumor residues.
- To provide surgeons with metrics for selecting optimal ablation paths for improved precision and efficiency.
Main Methods:
- Utilized point-cloud representations for tumor residue geometry, moving beyond analytical descriptions.
- Developed algorithms for generating and evaluating multiple path plans for robotic ablation.
- Integrated path planning with the RAVEN II surgical robot platform for simulated testing.
Main Results:
- Demonstrated robust path planning for irregularly shaped tumor residues using point-cloud data.
- Generated actionable metrics to aid surgeons in selecting the most effective ablation path.
- Successfully executed a semi-automated robotic brain tumor ablation procedure in a simulated environment.
Conclusions:
- Semi-automated robotic surgery with advanced path planning offers a promising approach to brain tumor margin resection.
- The presented methods enhance precision and efficiency in robotic tumor ablation, addressing limitations of manual and traditional robotic techniques.
