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Robot-assisted Ultrasound Reconstruction for Spine Surgery: from Bench-top to Pre-clinical Study
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  • Ruixuan Li ,
  • Ayoob Davoodi ,
  • Yuyu Cai ,
  • Kenan Niu ,
  • Gianni Borghesan ,
  • Nicola Cavalcanti ,
  • Aidana Massalimova ,
  • Fabio Carrillo ,
  • Philipp Fürnstahl ,
  • Emmanuel Vander Poorten
Ruixuan Li
KU Leuven, KU Leuven

Corresponding Author:[email protected]

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Ayoob Davoodi
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Kenan Niu
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Gianni Borghesan
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Nicola Cavalcanti
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Aidana Massalimova
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Fabio Carrillo
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Philipp Fürnstahl
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Emmanuel Vander Poorten
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Purpose: Robot-assisted ultrasound (US) systems could be used to provide a non-radiative three-dimensional (3D) reconstruction that can form the basis for guiding spine surgical procedures. Despite promising studies on this technology, there are few studies that offer insight into the robustness and generality of the approach by e.g. verifying performance in various testing scenarios. Therefore, this study provides an assessment of the robot-assisted US system, with technical details from experiments starting at the bench-top up to the pre-clinical study.
Methods: A semi-automatic control strategy is proposed to ensure continuous and smooth scanning. Next, a method based on U-Net was developed to automatically process the anatomic features and derive a high quality 3D US reconstruction. Experiments on phantoms and human cadavers validate the proposed approach.
Results: Average deviations of scanning force were found of 2.84 ± 0.45 N on synthetic phantoms and of 5.64 ± 1.10 N on human cadavers. The reconstruction yielded a mean 3D representation error of 1.28 ± 0.87 mm for the synthetic phantoms and of 1.74 ± 0.89 mm for the human cadavers.
Conclusion: These results show the proposed system has high safety performance and could keep the probe force stable within the range of 1 N to obtain a good reconstruction. The experiments indicate that the proposed robotassisted US approach works in quite different experimental settings. The results encourage to also explore the potential of this technology in in-vivo studies.
12 May 2023Published in International Journal of Computer Assisted Radiology and Surgery volume 18 issue 9 on pages 1613-1623. 10.1007/s11548-023-02932-z