Robust path planning for flexible needle insertion using Markov decision processes
| Autor: | Chee-Kong Chui, Pengqian Yu, Kah Bin Lim, Xiaoyu Tan |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Computer science Biomedical Engineering Soft tissue deformation Health Informatics 02 engineering and technology Imaging phantom Decision Support Techniques 030218 nuclear medicine & medical imaging Probability of success 03 medical and health sciences 020901 industrial engineering & automation 0302 clinical medicine Robustness (computer science) Humans Radiology Nuclear Medicine and imaging Motion planning Phantoms Imaging Control engineering Robotics General Medicine Needle steering Computer Graphics and Computer-Aided Design Markov Chains Computer Science Applications Needles Surgery Needle insertion Computer Vision and Pattern Recognition Markov decision process |
| Zdroj: | International Journal of Computer Assisted Radiology and Surgery. 13:1439-1451 |
| ISSN: | 1861-6429 1861-6410 |
| DOI: | 10.1007/s11548-018-1783-x |
| Popis: | Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue–needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue–needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue–needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation. |
| Databáze: | OpenAIRE |
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