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Global optimization point-set registration based on translation/rotation decoupling for image-guided surgery

Kexue Fu1,2, Xinrong Chen2,3, Manning Wang1,2

  • 1Digital Medical Research Center of School of Basic Medical Sciences, Fudan University, Shanghai, China.

Medical Physics
|June 30, 2022
PubMed
Summary

This study introduces a novel rotation-invariant feature for image-to-patient registration, improving accuracy and speed. The method effectively decouples rotation and translation, enabling global optimization for image-guided surgery.

Keywords:
global optimization point set registrationimage-guided surgery systemimage-to-patient space registrationtranslation rotation decoupling

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Area of Science:

  • Medical image analysis
  • Computer-assisted surgery
  • Geometric registration algorithms

Background:

  • Image-guided surgery relies on accurate spatial registration between medical images and the patient.
  • Existing point or surface matching methods in neurosurgery often fail to achieve global optimization.
  • A key challenge is the decoupling of rotation and translation for robust registration.

Purpose of the Study:

  • To propose a novel rotation-invariant feature for decoupling rotation and translation in image-to-patient spatial registration.
  • To develop a global optimization point set registration method based on these new features.
  • To enhance the accuracy and efficiency of image-guided surgery systems.

Main Methods:

  • Constructed rotation-invariant features using edges and angles, offering high resolution.
  • Incorporated translation invariance for some features.
  • Employed a branch and bound search strategy for global optimization and reduced computational cost.

Main Results:

  • The proposed method achieved higher accuracy and faster execution times compared to Iterative Closest Point (ICP) and Coherent Point Drift (CPD) methods.
  • Demonstrated an average rotation error of 0.124 degrees and translation error of 0.38 mm on clinical data.
  • Provided a good initial pose for ICP, accelerating its convergence to the global optimum.

Conclusions:

  • The surface registration method based on translation-rotation decoupling significantly improves registration accuracy.
  • The proposed approach offers superior time efficiency in image-to-patient spatial registration.
  • This method enhances the reliability and performance of image-guided surgical navigation.