Paper
22 March 2010 Adaptive modulation of bilateral filtering based on a practical noise model for streaking and noise reduction in multi-slice CT
Lifeng Yu, Armando Manduca, Megan Jacobsen, Joshua D. Trzasko, Joel G. Fletcher, David R. DeLone, Cynthia H. McCollough
Author Affiliations +
Abstract
We have recently developed a locally-adaptive method for noise control in CT based upon bilateral filtering. Different from the previous adaptive filters, which were locally adaptive by adjusting the filter strength according to local photon statistics, our use of bilateral filtering in projection data incorporates a practical CT noise model and takes into account the local structural characteristics, and thus can preserve edge information in the projection data and maintain the spatial resolution. Despite the incorporation of the CT noise model and local structural characteristics in the bilateral filtering, the noise-resolution properties of the filtered image are still highly dependent on predefined parameters that control the weighting factors in the bilateral filtering. An inappropriate selection of these parameters may result in a loss of spatial resolution or an insufficient reduction of noise. In this work, we employed an adaptive strategy to modulate the bilateral filtering strength according to the noise-equivalent photon numbers determined from each projection measurement. We applied the proposed technique to head/neck angiographic CT exams, which had highly non-uniform attenuation levels during the scan. The results demonstrated that the technique can effectively reduce the noise and streaking artifacts caused by high attenuation, while maintaining the reconstruction accuracy in less attenuating regions.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lifeng Yu, Armando Manduca, Megan Jacobsen, Joshua D. Trzasko, Joel G. Fletcher, David R. DeLone, and Cynthia H. McCollough "Adaptive modulation of bilateral filtering based on a practical noise model for streaking and noise reduction in multi-slice CT", Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76222O (22 March 2010); https://doi.org/10.1117/12.845403
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CITATIONS
Cited by 4 scholarly publications and 2 patents.
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KEYWORDS
Digital filtering

Image filtering

Denoising

Computed tomography

Modulation

Data modeling

Signal attenuation

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