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A Concentric Tube Continuum Robot with Piezoelectric Actuation for MRI-Guided Closed-Loop Targeting

Overview of attention for article published in Annals of Biomedical Engineering, March 2016
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Title
A Concentric Tube Continuum Robot with Piezoelectric Actuation for MRI-Guided Closed-Loop Targeting
Published in
Annals of Biomedical Engineering, March 2016
DOI 10.1007/s10439-016-1585-7
Pubmed ID
Authors

Hao Su, Gang Li, D. Caleb Rucker, Robert J. Webster III, Gregory S. Fischer

Abstract

This paper presents the design, modeling and experimental evaluation of a magnetic resonance imaging (MRI)-compatible concentric tube continuum robotic system. This system enables MRI-guided deployment of a precurved and steerable concentric tube continuum mechanism, and is suitable for clinical applications where a curved trajectory is needed. This compact 6 degree-of-freedom (DOF) robotic system is piezoelectrically-actuated, and allows simultaneous robot motion and imaging with no visually observable image artifact. The targeting accuracy is evaluated with optical tracking system and gelatin phantom under live MRI-guidance with Root Mean Square (RMS) errors of 1.94 and 2.17 mm respectively. Furthermore, we demonstrate that the robot has kinematic redundancy to reach the same target through different paths. This was evaluated in both free space and MRI-guided gelatin phantom trails, with RMS errors of 0.48 and 0.59 mm respectively. As the first of its kind, MRI-guided targeted concentric tube needle placements with ex vivo porcine liver are demonstrated with 4.64 mm RMS error through closed-loop control of the piezoelectrically-actuated robot.

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The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 77 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 26%
Student > Master 11 14%
Researcher 10 13%
Professor > Associate Professor 7 9%
Student > Doctoral Student 5 6%
Other 10 13%
Unknown 15 19%
Readers by discipline Count As %
Engineering 44 56%
Medicine and Dentistry 7 9%
Computer Science 5 6%
Psychology 1 1%
Mathematics 1 1%
Other 2 3%
Unknown 18 23%