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Publication Detail
Validation of a two- to three-dimensional registration algorithm for aligning preoperative CT images and intraoperative fluoroscopy images.
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Journal Article
  • Authors:
    Penney GP, Batchelor PG, Hill DL, Hawkes DJ, Weese J
  • Publication date:
    06/2001
  • Pagination:
    1024, 1032
  • Journal:
    Med Phys
  • Volume:
    28
  • Issue:
    6
  • Status:
    Published
  • Country:
    United States
  • Print ISSN:
    0094-2405
  • Language:
    eng
  • Keywords:
    Algorithms, Biophysical Phenomena, Biophysics, Fluoroscopy, Humans, Radiographic Image Interpretation, Computer-Assisted, Radiotherapy Planning, Computer-Assisted, Tomography, X-Ray Computed
Abstract
We present a validation of an intensity based two- to three-dimensional image registration algorithm. The algorithm can register a CT volume to a single-plane fluoroscopy image. Four routinely acquired clinical data sets from patients who underwent endovascular treatment for an abdominal aortic aneurysm were used. Each data set was comprised of two intraoperative fluoroscopy images and a preoperative CT image. Regions of interest (ROI) were drawn around each vertebra in the CT and fluoroscopy images. Each CT image ROI was individually registered to the corresponding ROI in the fluoroscopy images. A cross validation approach was used to obtain a measure of registration consistency. Spinal movement between the preoperative and intraoperative scene was accounted for by using two fluoroscopy images. The consistency and robustness of the algorithm when using two similarity measures, pattern intensity and gradient difference, was investigated. Both similarity measures produced similar results. The consistency values were rotational errors below 0.74 degree and in-plane translational errors below 0.90 mm. These errors approximately relate to a two-dimensional projection error of 1.3 mm. The failure rate was less than 8.3% for three of the four data sets. However, for one of the data sets a much larger failure rate (28.5%) occurred.
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