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Fiducial-based registration with a touchable region model.

Sungmin Kim1, Peter Kazanzides2

  • 1Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA. sungminkim@jhu.edu.

International Journal of Computer Assisted Radiology and Surgery
|September 2, 2016
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Summary

This study introduces a new registration framework to improve accuracy in image-guided surgery. The iterative closest touchable point (ICTP) method reduces errors from manual fiducial localization, leading to more consistent surgical navigation.

Keywords:
Fiducial markerRegistrationSurgical navigationSurgical robot

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Area of Science:

  • Medical Imaging
  • Surgical Navigation
  • Image-Guided Surgery

Background:

  • Image-guided surgery relies on accurate registration between preoperative images and the intraoperative coordinate system.
  • Manual fiducial localization in current methods introduces user-dependent errors, compromising registration accuracy.
  • A need exists for registration techniques tolerant of imprecise fiducial localization.

Purpose of the Study:

  • To develop and evaluate a novel registration framework, the iterative closest touchable point (ICTP), designed to mitigate localization errors.
  • To enhance the accuracy and consistency of image-guided surgery by reducing user dependency.

Main Methods:

  • The ICTP framework employs model-based localization and a touchable region model.
  • It involves three stages: fiducial marker localization in image space, initial paired-point registration, and iterative closest point-based fine registration.

Main Results:

  • Phantom experiments demonstrated that ICTP improves accuracy compared to standard paired-point registration.
  • ICTP shows particular benefit when significant localization errors are introduced by the surgeon.
  • Accuracy improvements were observed using a common neurosurgical fiducial marker design.

Conclusions:

  • The proposed ICTP method effectively reduces the impact of surgeon localization performance on registration accuracy.
  • This leads to more consistent and less user-dependent registration outcomes in image-guided surgery.
  • ICTP offers a more robust solution for surgical navigation and robotic systems.