Literature DB >> 29752637

Robust path planning for flexible needle insertion using Markov decision processes.

Xiaoyu Tan1, Pengqian Yu2, Kah-Bin Lim3, Chee-Kong Chui3.   

Abstract

PURPOSE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.

Keywords:  Markov decision processes; Needle steering; Robust planning; Tool–tissue interaction; Uncertainty

Mesh:

Year:  2018        PMID: 29752637     DOI: 10.1007/s11548-018-1783-x

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


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  1 in total

1.  Robot-assisted flexible needle insertion using universal distributional deep reinforcement learning.

Authors:  Xiaoyu Tan; Yonggu Lee; Chin-Boon Chng; Kah-Bin Lim; Chee-Kong Chui
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-11-25       Impact factor: 2.924

  1 in total

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