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General first-order target registration error model considering a coordinate reference frame in an image-guided

Zhe Min1, Max Q-H Meng2,3

  • 1Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, N.T., Hong Kong.

Medical & Biological Engineering & Computing
|October 8, 2020
PubMed
Summary

This study introduces an improved target registration error (TRE) estimation algorithm for image-guided surgery (IGS). The new method accurately models heterogeneous fiducial localization error (FLE) in surgical navigation systems.

Keywords:
Coordinate reference frameN-ocular tracking systemTarget registration error model

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Area of Science:

  • Medical image analysis
  • Surgical navigation systems

Background:

  • Point-based rigid registration (PBRR) is crucial in image-guided surgery (IGS).
  • Accurate target registration error (TRE) estimation is vital for surgical tool-tip tracking and image registration.
  • Surgical tool pose is often reported relative to a coordinate reference frame (CRF).
  • Fiducial localization error (FLE) in tracking systems can be inhomogeneous and anisotropic.

Purpose of the Study:

  • To extend the TRE estimation algorithm relative to a CRF for heterogeneous FLE cases.
  • To develop a model for TRE considering a CRF in surgical navigation.
  • To enhance the accuracy of surgical tool-tip tracking error estimation.

Main Methods:

  • Developed an extended TRE estimation algorithm for CRFs, accommodating heterogeneous FLE.
  • Incorporated arbitrary weightings in solving registration problems within the algorithm.
  • Utilized Monte Carlo simulations to validate the algorithm's performance.

Main Results:

  • The proposed algorithm effectively estimates TRE for both homogeneous and inhomogeneous FLE distributions.
  • Performance is comparable to existing methods for anisotropic, homogeneous FLE.
  • Outperforms classical algorithms in heterogeneous FLE cases with ideal weighting schemes.

Conclusions:

  • The novel TRE estimation algorithm enhances accuracy in surgical navigation, particularly with complex FLE.
  • Enables more reliable online estimation of surgical tool-tip tracking error in IGS.
  • Clinical applications include improved decision-making for surgeons during procedures.