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International Journal of Computer Assisted Radiology and Surgery

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09-12-2023 | Silicone | Original Article

Online advance respiration prediction model for percutaneous puncture robotics

Authors: Yanping Lin, Jin Guo, Xu Yang, Wangjie Xu, Zhaojun Li

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 3/2024

Abstract

Purpose

Surgical robots have significant research value and clinical significance in the field of percutaneous punctures. There have been numerous studies on ultrasound-guided percutaneous surgical robots; however, addressing the respiratory compensation problem of deep punctures remains a significant obstacle. Herein we propose a robotic system for percutaneous puncture with respiratory compensation.

Methods

We proposed an online advance respiratory prediction model based on Bidirectional Gate Recurrent Unit (Bi-GRU) for the respiratory prediction requirements of surgical robot systems. By analyzing the main factors governing the accuracy of the respiratory motion prediction models, various parameters of the online advance prediction model were optimized. Subsequently, we integrated and developed ultrasound-guided percutaneous puncture robot software and a hardware platform to implement respiratory compensation, thus verifying the effectiveness and reliability of various key technologies in the system.

Results

The proposed respiratory prediction model has a significantly reduced update time, with an average root mean square error (RMSE) of less than 0.4 mm. This represents a reduction of ~ 20% compared to the online training long short-term memory(LSTM). By conducting puncture experiments based on a respiratory phantom, the average puncture error was 2.71 ± 0.65 mm and the average single-round puncture time was 65.00 ± 6.67 s.

Conclusion

Herein we proposed and optimized an online training respiratory prediction network model based on Bi-GRU. The stability and reliability of this system are verified by conducting puncture experiments on a respiratory phantom.

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Title: Online advance respiration prediction model for percutaneous puncture robotics
Authors: Yanping Lin
Jin Guo
Xu Yang
Wangjie Xu
Zhaojun Li
Publication date: 09-12-2023
Publisher: Springer International Publishing
Keyword: Silicone
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 3/2024
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-023-03041-7

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Online advance respiration prediction model for percutaneous puncture robotics

Abstract

Purpose

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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