Advertisement

Fourier-based Reduction of Directed Streak Artifacts in Cone-Beam CT

  • Julia Gawellek
  • Bastian Bier
  • Garry Gold
  • Andreas Maier
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

Due to its adjustable scan trajectory, C-arm cone-beam CT has been used recently to acquire knee scans in an upright position. However, stabilization devices located outside the FOV introduce streak artifacts in the reconstructed images. This paper proposes a method to remove those streak artifacts. Using selective filtering of the Fourier transforms of the reconstructions, we propose a filter design that attenuates the frequencies that are responsible for the streak artifacts. The filter is constructed by taking both the frequency and the orientation of the introduced streaks into account. We compare our approach to a bandpass-filter. Our proposed method is able to reduce the streaks in the reconstruction remarkably while preserving edge information, whereas the bandpass-filter is not capable of preserving sharp edges in the filtered image. Moreover, our method yields an improved SSIM when comparing both filter techniques to simulated ground truth data.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur

  1. 1.
    Choi JH, Maier A, Keil A, et al. Fiducial marker-based correction for involuntary motion in weight-bearing c-arm ct scanning of knees. II. experiment. Med Phy. 2014;41(6).Google Scholar
  2. 2.
    Abdoli M, Dierckx RA, Zaidi H. Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging. Med Phys. 2012;39(6):3343–3360.Google Scholar
  3. 3.
    Galigekere R, Wiesent K, Holdsworth D. Techniques to alleviate the effects of view aliasing artifacts in computed tomography. Med Phys. 1999;26(6):896–904.Google Scholar
  4. 4.
    Bier B, Mualla F, Steidl S, et al.; Springer. Band-Pass filter design by segmentation in frequency domain for detection of epithelial cells in endomicroscope images. Proc BVM. 2015; p. 413–418.Google Scholar
  5. 5.
    Smith SW. The Scientist and Engineer’s Guide to Digital Signal Processing. San Diego: California Technical Pub. San Diego; 1997.Google Scholar

Copyright information

© Springer-Verlag GmbH Deutschland 2018

Authors and Affiliations

  • Julia Gawellek
    • 1
  • Bastian Bier
    • 1
  • Garry Gold
    • 2
  • Andreas Maier
    • 1
  1. 1.Pattern Recognition LabFriedrich-Alexander-University Erlangen-NurembergErlangenDeutschland
  2. 2.Radiological Sciences LaboratoryStanford UniversitystanfordUSA

Personalised recommendations