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Fusion of Biplane Fluoroscopy with Fiber Bragg Grating for 3D Catheter Shape Reconstruction

  • M. Ourak*
  • , S. De Buck
  • , X. T. Ha
  • , O. Al-Ahmad
  • , K. Bamps
  • , J. Ector
  • , E. Vander Poorten
  • *Corresponding author for this work
  • Robot Assisted Surgery (RAS)
  • KU Leuven
  • Department of Cardiology

Research output: Contribution to journal › Article › peer-review

Abstract

Nowadays, navigating therapeutic catheters takes place under 2D fluoroscopic imaging. This requires considerable training of the clinician and exposes him/her to X-ray radiation. Researchers have increasingly investigated alternative sensing techniques. In this respect, Fiber Bragg Grating (FBG)-based shape sensing is gaining popularity. This letter proposes two approaches to fuse FBG with fluoroscropy, improve the understanding of the 3-dimensional shape while reducing fluoroscopy use. This letter proposes two FBG-fluoroscopy fusion approaches that combine fluoroscopy and FBG measurements. A comparison is performed between 3D shape reconstructions based on biplane fluoroscopy, rigidly fused multi-core FBG and dynamically fused FBG shape reconstruction. To verify the performance of the different approaches experiments were performed with custom made catheter in a CathLab on 3D printed tubes with known ground truth shape. The experiments showed overall acceptable errors for the targeted application with a maximum below 2 mm. The error of shape reconstruction through biplane fluoroscopy, rigid and dynamic fusion were found to be 1.51\pm 0.04 mm, 1.77\pm 0.29 mm and 1.47\pm 0.15 mm, respectively. Thus, FBG-fluoroscopy fusion offers comparable results to fluoroscopy and may substantially reduce the radiation dose through optimal acquisition frequency.

Original languageEnglish
Article number9472933
Pages (from-to)6505-6512
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume6
Issue number4
DOIs
Publication statusPublished - Oct 2021
Externally publishedYes

Keywords

  • Steerable catheters
  • performance evaluation and benchmarking
  • sensor fusion
  • surgical robotics

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