Paper
3 July 2001 Reduction of noise and image artifacts in computed tomography by nonlinear filtration of projection images
Omer Demirkaya
Author Affiliations +
Abstract
This study investigates the efficacy of filtering two-dimensional (2D) projection images of Computer Tomography (CT) by the nonlinear diffusion filtration in removing the statistical noise prior to reconstruction. The projection images of Shepp-Logan head phantom were degraded by Gaussian noise. The variance of the Gaussian distribution was adaptively changed depending on the intensity at a given pixel in the projection image. The corrupted projection images were then filtered using the nonlinear anisotropic diffusion filter. The filtered projections as well as original noisy projections were reconstructed using filtered backprojection (FBP) with Ram-Lak filter and/or Hanning window. The ensemble variance was computed for each pixel on a slice. The nonlinear filtering of projection images improved the SNR substantially, on the order of fourfold, in these synthetic images. The comparison of intensity profiles across a cross-sectional slice indicated that the filtering did not result in any significant loss of image resolution.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Omer Demirkaya "Reduction of noise and image artifacts in computed tomography by nonlinear filtration of projection images", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.430964
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Cited by 40 scholarly publications and 1 patent.
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KEYWORDS
Image filtering

Nonlinear filtering

Computed tomography

Anisotropic filtering

Diffusion

Image processing

Anisotropic diffusion

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