A New Method for Reducing Metal Artifacts of Flat Workpiece in Cone-Beam CT

  • Feng Zhang
  • Li-zhong Lu
  • Qing-liang Li
  • Bin Yan
  • Lei Li
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 125)

Abstract

Metal artifacts of flat workpiece often exist in the horizontal direction in cone-beam Computed Tomography (CT) caused by beam-hardening, photon starvation, etc. In this paper, a novel method for reducing metal artifacts of flat workpiece is presented. In the proposed algorithm, firstly the 3-D image is reconstructed after normal scanning. Secondly, the flat workpiece which was rotated by ninety degrees is scanned again and the new 3-D reconstructed image is obtained. Thirdly, Scale- Invariant Feature Transform (SIFT) algorithmis adopted to match the slice image of the first reconstructed image with the slice image of the second one exactly. Finally, image fusion technique is applied to produce a fused image with less metal artifacts. The experiments have shown that the proposed method improves the reconstructed image quality greatly, and provides more detailed information compared to the current Metal Artifacts Reduction (MAR) algorithms.

Keywords

Image Fusion Metal Artifact Algebraic Reconstruction Technique Reduce Metal Artifact Image Fusion Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kalender, A., Hebel, R., Ebersberger, J.: Reduction of CT artifacts caused by metallic implants. Radiology 2, 576–577 (1987)Google Scholar
  2. 2.
    Zhao, S., Douglas, D., et al.: X-ray CT metal artifacts reduction using wavelets: An application for imaging total hip prostheses. IEEE Transactions on Medical Imaging 19, 1238–1247 (2000)CrossRefGoogle Scholar
  3. 3.
    Wei, J., Chen, L., Sandison, G., Liang, L.: X-ray CT high density artifact suppression in the presence of bones. Physics in Medicine and Biology 49, 5407–5418 (2004)CrossRefGoogle Scholar
  4. 4.
    Gordon, R., Bender, R., Herman, G.: Algebraic reconstruction techniques (ART) for the three-dimensional electron microscopy and X-ray photography. Theor. Biol. 29, 471–481 (1970)CrossRefGoogle Scholar
  5. 5.
    Andersen, A., Kak, A.: Simultaneous algebraic reconstruction technique (SART): A new implementation of the ART algorithm. Ultrason. Imag. 6, 81–94 (1984)CrossRefGoogle Scholar
  6. 6.
    Wang, G., Snyder, D.L., O’Sullivan, J.A., Vannier, M.W.: Iterative Deblurring for CT Metal Artifact Reduction. IEEE Transactions on Medical Imaging 15, 657–664 (1996)CrossRefGoogle Scholar
  7. 7.
    Xia, D., Roeske, J., et al.: A hybrid approach to reducing computed tomography metal artifacts in intracavitary brachytherapy. Brachytherapy 4, 18–23 (2005)CrossRefGoogle Scholar
  8. 8.
    Lemmens, C., Faul, D., Nuyts, J.: Suppression of Metal Artifacts in CT Using a Reconstruction Procedure That Combines MAP and Projection Completion. IEEE Transactions on Medical Imaging 28, 250–260 (2008)CrossRefGoogle Scholar
  9. 9.
    Lowe, D.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60, 91–110 (2004)CrossRefGoogle Scholar
  10. 10.
    Pohl, C., Genderen, J.: Multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing 5, 823–854 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Feng Zhang
    • 1
  • Li-zhong Lu
    • 1
  • Qing-liang Li
    • 1
  • Bin Yan
    • 1
  • Lei Li
    • 1
  1. 1.National Digital Switching System Engineering & Technology Research CenterZhengzhouChina

Personalised recommendations