Reducing windmill artifacts in clinical spiral CT using a deep learning-based projection raw data upsampling: Method and robustness evaluation.

Journal: Medical physics
PMID: 38227833

Abstract

BACKGROUND: Multislice spiral computed tomography (MSCT) requires an interpolation between adjacent detector rows during backprojection. Not satisfying the Nyquist sampling condition along the z-axis results in aliasing effects, also known as windmill artifacts. These image distortions are characterized by bright streaks diverging from high contrast structures.

Authors

  • Jan Magonov
    Division of X-Ray Imaging and Computed Tomography, German Cancer Research Center (DKFZ) Heidelberg, Heidelberg, Germany.
  • Joscha Maier
    German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Julien Erath
    German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Johan Sunnegårdh
    Computed Tomography Division, Siemens Healthineers AG, Forchheim, Germany.
  • Eric Fournié
    Siemens Healthineers, Forchheim, Germany.
  • Karl Stierstorfer
    Siemens Healthineers, Forchheim, Germany.
  • Marc Kachelrieß
    German Cancer Research Center, Heidelberg, 69120, Germany.

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