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Neurosurgical robotic arm drilling navigation system
Chung-Chih Lin1,2, Hsin-Cheng Lin1, Wen-Yo Lee3
1Department of Computer Science and Information Engineering, College of Engineering, Chang Gung University, Taiwan.
Background:
The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process.
Methods:
The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled-through. Three kinds of experiment were designed.
Results:
The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto-stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non-drilled-through cases (8.42% and 4.21% in control groups 1 and 2).
Conclusions:
The system may be useful for neurosurgical robotic arm drilling navigation.
