DWI denoising using spatial, angular, and radiometric filtering

Authors:
Pew-Thian Yap;Dinggang Shen
Affiliations:
Department of Radiology and Biomedical Research Imaging Center (BRIC), The University of North Carolina at Chapel Hill;Department of Radiology and Biomedical Research Imaging Center (BRIC), The University of North Carolina at Chapel Hill
Venue:
MBIA'12 Proceedings of the Second international conference on Multimodal Brain Image Analysis
Year:
2012

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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.