Gradient-based 2-D/3-D rigid registration of fluoroscopic X-ray to CT

Harel Livyatan, Ziv Yaniv, Leo Joskowicz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

158 Scopus citations

Abstract

We present a gradient-based method for rigid registration of a patient preoperative computed tomography (CT) to its intraoperative situation with a few fluoroscopic X-ray images obtained with a tracked C-arm. The method is noninvasive, anatomy-based, requires simple user interaction, and includes validation. It is generic and easily customizable for a variety of routine clinical uses in orthopaedic surgery. Gradient-based registration consists of three steps: 1) initial pose estimation; 2) coarse geometry-based registration on bone contours, and; 3) fine gradient projection registration (GPR) on edge pixels. It optimizes speed, accuracy, and robustness. Its novelty resides in using volume gradients to eliminate outliers and foreign objects in the fluoroscopic X-ray images, in speeding up computation, and in achieving higher accuracy. It overcomes the drawbacks of intensity-based methods, which are slow and have a limited convergence range, and of geometry-based methods, which depend on the image segmentation quality. Our simulated, in vitro, and cadaver experiments on a human pelvis CT, dry vertebra, dry femur, fresh lamb hip, and human pelvis under realistic conditions show a mean 0.5-1.7 mm (0.5-2.6 mm maximum) target registration accuracy.

Original languageAmerican English
Pages (from-to)1395-1406
Number of pages12
JournalIEEE Transactions on Medical Imaging
Volume22
Issue number11
DOIs
StatePublished - Nov 2003

Bibliographical note

Funding Information:
Manuscript received June 4, 2003; revised August 4, 2003. This research was supported in part by a grant from the Israel Ministry of Industry and Trade for the IZMEL Consortium on Image-Guided Therapy. Asterisk indicates corresponding author.

Keywords

  • 2D/3D rigid registration
  • Fluoroscopic X-ray to CT registration
  • Gradient based
  • Image registration

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