A Framework of State Estimation on Laminar Grinding Based on the CT Image-Force Model
Jihao Liu1, Guoyan Zheng2, Weixin Yan3
1State Key Laboratory of Ocean Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Sensors (Basel, Switzerland)
|January 11, 2025
Summary
Accurately localizing the cutting tip during bone grinding surgery is crucial for safety. This study presents a novel framework using CT images and milling force data to estimate the cutting tip's position, enhancing surgical precision.
Area of Science:
- Surgical Technology
- Biomedical Engineering
- Medical Imaging
Background:
- Precise localization of surgical tools, specifically the cutting tip during bone grinding, remains a significant challenge for ensuring surgical safety.
- Existing methods may lack the real-time accuracy needed for complex laminar grinding procedures.
Purpose of the Study:
- To develop and validate a framework for accurate state estimation of the cutting tip during laminar grinding.
- To integrate pre-operative CT imaging with intra-operative milling force data for enhanced surgical guidance.
Main Methods:
- A CT image-force model framework was developed, utilizing pre-operative CT scans and intra-operative milling force signals.
- A bone milling force prediction model was established to translate surgical paths into predicted force sequences.
- The tumbling window algorithm segmented intra-operative force signals, and dynamic time warping (DTW) calculated similarity to predicted sequences.
- Random Sample Consensus (RANSAC) was employed to mitigate the influence of external factors and improve robustness.
Main Results:
- The developed framework successfully estimates the cutting tip's position by deriving similarity between predicted and segmented milling force signals.
- The integration of CT imaging and force feedback provides a robust method for real-time tool localization.
- RANSAC improved the reliability of the estimation in the presence of signal noise or variations.
Conclusions:
- The proposed framework offers a promising solution for precise cutting tip localization in bone grinding surgeries.
- This approach has the potential to significantly improve surgical safety and accuracy in orthopedic and neurosurgical procedures.
- The open-sourced code facilitates further research and development in image-guided surgical interventions.
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