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DWI Denoising Using Spatial, Angular, and Radiometric Filtering

  • Pew-Thian Yap
  • Dinggang Shen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7509)

Abstract

In this paper, we study the effectiveness of the concurrent utilization of spatial, angular, and radiometric (SAR) information for denoising diffusion-weighted data. SAR filtering smooths diffusion-weighted images while at the same time preserves edges by means of nonlinear combination of nearby and similar signal values. The method is noniterative, local, and simple. It combines diffusion signals based on both their spatio-angular closeness and their radiometric similarity, with greater preference given to nearby and similar values. Our results suggest that SAR filtering reveals structures that are concealed by noise and produces anisotropy maps with markedly improved quality.

Keywords

Gray Matter Angular Component Rician Noise Voxel Location Denoising Scheme 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pew-Thian Yap
    • 1
  • Dinggang Shen
    • 1
  1. 1.Department of Radiology and Biomedical Research Imaging Center (BRIC)The University of North Carolina at Chapel HillU.S.A.

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