An Autonomous Fluoroscopic Imaging System for Catheter Insertions by Bilateral Control Scheme: A Numerical Simulation Study

This study presents a bilateral control architecture that links fluoroscopic image feedback directly to the kinematics of a tendon-driven, three-joint robotic catheter and a 3-DoF motorised C-arm, intending to preserve optimal imaging geometry during autonomous catheter insertion and thereby mitigating radiation exposure. Forward and inverse kinematics for both manipulators were derived via screw theory and geometric analysis, while a calibrated projection model generated synthetic X-ray images whose catheter bending angles were extracted through intensity thresholding, segmentation, skeletonisation, and least-squares circle fitting. The estimated angle fed a one-dimensional extremum-seeking routine that rotated the C-arm about its third axis until the apparent bending angle peaked, signalling an orthogonal view of the catheter’s bending plane. Implemented in a physics-based simulator, the framework achieved inverse-kinematic errors below 0.20% for target angles between 20° and 90°, with accuracy decreasing to 3.00% at 10°. The image-based angle estimator maintained a root-mean-square error ≤3% across most of the same range, rising to 6.4% at 10°. The C-arm search consistently located the optimal perspective, and the combined controller steered the catheter tip along a predefined aortic path without collision. These results demonstrate sub-degree angular accuracy under idealised, noise-free conditions and validate real-time coupling of image guidance to dual-manipulator motion; forthcoming work will introduce realistic image noise, refined catheter mechanics, and hardware-in-the-loop testing to confirm radiation-dose and workflow benefits.

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Publication Details

Journal
Machines
Published
2025-06-06
DOI
https://doi.org/10.3390/machines13060498
Citations
1
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.67
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article

An Autonomous Fluoroscopic Imaging System for Catheter Insertions by Bilateral Control Scheme: A Numerical Simulation Study

Kenan Niu, Dezhi Sun, G. Ward
1 citations
Machines
Soft Robotics and Applications
0.67
article

An Autonomous Fluoroscopic Imaging System for Catheter Insertions by Bilateral Control Scheme: A Numerical Simulation Study

Kenan Niu, Dezhi Sun, G. Ward
article en
1 citations

Abstract

This study presents a bilateral control architecture that links fluoroscopic image feedback directly to the kinematics of a tendon-driven, three-joint robotic catheter and a 3-DoF motorised C-arm, intending to preserve optimal imaging geometry during autonomous catheter insertion and thereby mitigating radiation exposure. Forward and inverse kinematics for both manipulators were derived via screw theory and geometric analysis, while a calibrated projection model generated synthetic X-ray images whose catheter bending angles were extracted through intensity thresholding, segmentation, skeletonisation, and least-squares circle fitting. The estimated angle fed a one-dimensional extremum-seeking routine that rotated the C-arm about its third axis until the apparent bending angle peaked, signalling an orthogonal view of the catheter’s bending plane. Implemented in a physics-based simulator, the framework achieved inverse-kinematic errors below 0.20% for target angles between 20° and 90°, with accuracy decreasing to 3.00% at 10°. The image-based angle estimator maintained a root-mean-square error ≤3% across most of the same range, rising to 6.4% at 10°. The C-arm search consistently located the optimal perspective, and the combined controller steered the catheter tip along a predefined aortic path without collision. These results demonstrate sub-degree angular accuracy under idealised, noise-free conditions and validate real-time coupling of image guidance to dual-manipulator motion; forthcoming work will introduce realistic image noise, refined catheter mechanics, and hardware-in-the-loop testing to confirm radiation-dose and workflow benefits.

MachinesVol. 13(6)
University of Twente (NL)
Openalex Percentile: Top 31%
Soft Robotics and Applications
0.67
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