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Association between pedicle screw dimensions and pedicle morphometry in computed tomography scans.

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Related Experiment Video

Updated: Jun 29, 2026

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
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Feature-based multimodal 3D/2D and 3D/3D registration framework for pedicle screw registration and evaluation.

Usha Kiran1, H Anitha2, Shyamasunder N Bhat3

  • 1Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.

European Spine Journal : Official Publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
|September 13, 2025
PubMed
Summary

This study introduces a novel feature-based registration framework for spine surgery. It accurately estimates pedicle screw trajectories using pre-operative MR and intra-operative X-ray images, enhancing surgical precision.

Keywords:
3D to 3D registrationPedicle screw registrationTrajectory ErrorVertebral endplate registrationVertebral pose estimation

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Area of Science:

  • Medical Imaging
  • Spine Surgery
  • Computer-Aided Surgery

Background:

  • Accurate pedicle screw placement is critical for spine surgery safety.
  • Multimodal image registration faces challenges like intensity mismatches and tissue non-correspondence.

Purpose of the Study:

  • Develop and validate a feature-based 3D to 2D registration framework.
  • Integrate pre-operative MR with intra-operative X-ray for pedicle screw trajectory estimation.
  • Achieve robust 3D visualization and overcome multimodal registration limitations.

Main Methods:

  • Utilized vertebral endplates as consistent features for registration.
  • Employed forward projection of segmented MR images and binary image matching.
  • Optimized registration using CMA-ES and validated with 3D to 3D registration against CT.

Main Results:

  • The framework accurately estimated pedicle screw trajectories with errors below 2.5 mm.
  • Demonstrated precise alignment of trajectory positions across different imaging modalities.
  • Validated accuracy through 3D to 3D registration of pre-operative MR and post-operative CT.

Conclusions:

  • The feature-based registration framework offers fast and accurate 3D trajectory information for spine navigation.
  • This method enhances surgical precision and provides reliable evaluation metrics.
  • It serves as a valuable tool for clinical diagnosis in pedicle screw placement procedures.