Article ; Online: Inverse Reinforcement Learning Intra-Operative Path Planning for Steerable Needle.
IEEE transactions on bio-medical engineering
2022 Volume 69, Issue 6, Page(s) 1995–2005
Abstract: Objective: This paper presentsa safe and effective keyhole neurosurgery intra-operative planning framework for flexible neurosurgical robots. The framework is intended to support neurosurgeons during the intra-operative procedure to react to a dynamic ... ...
| Abstract | Objective: This paper presentsa safe and effective keyhole neurosurgery intra-operative planning framework for flexible neurosurgical robots. The framework is intended to support neurosurgeons during the intra-operative procedure to react to a dynamic environment. Methods: The proposed system integrates inverse reinforcement learning path planning algorithm combined with 1) a pre-operative path planning framework for fast and intuitive user interaction, 2) a realistic, time-bounded simulator based on Position-based Dynamics (PBD) simulation that mocks brain deformations due to catheter insertion and 3) a simulated robotic system. Results: Simulation results performed on a human brain dataset show that the inverse reinforcement learning intra-operative planning method can guide a steerable needle with bounded curvature to a predefined target pose with an average targeting error of 1.34 ± 0.52 (25 Conclusion: With this work, we demonstrate that the presented intra-operative steerable needle path planner is able to avoid anatomical obstacles while optimising surgical criteria. Significance: The results demonstrate that the proposed method is fast and can securely steer flexible needles with high accuracy and robustness. |
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| MeSH term(s) | Algorithms ; Brain/surgery ; Computer Simulation ; Humans ; Needles | |||||
| Language | English | |||||
| Publishing date | 2022-05-19 | |||||
| Publishing country | United States | |||||
| Document type | Journal Article ; Research Support, Non-U.S. Gov't | |||||
| ZDB-ID | 160429-6 | |||||
| ISSN | 1558-2531 ; 0018-9294 | |||||
| ISSN (online) | 1558-2531 | |||||
| ISSN | 0018-9294 | |||||
| DOI | 10.1109/TBME.2021.3133075 | |||||
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| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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