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Modified Wiener method in diffusion weighted image denoising

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Abstract

To denoise the diffusion weighted images (DWIs) featured as multi-boundary, which was very important for the calculation of accurate DTIs (diffusion tensor magnetic resonance imaging), a modified Wiener filter was proposed. Through analyzing the widely accepted adaptive Wiener filter in image denoising fields, which suffered from annoying noise around the edges of DWIs and in turn greatly affected the denoising effect of DWIs, a local-shift method capable of overcoming the defect of the adaptive Wiener filter was proposed to help better denoising DWIs and the modified Wiener filter was constructed accordingly. To verify the denoising effect of the proposed method, the modified Wiener filter and adaptive Wiener filter were performed on the noisy DWI data, respectively, and the results of different methods were analyzed in detail and put into comparison. The experimental data show that, with the modified Wiener method, more satisfactory results such as lower non-positive tensor percentage and lower mean square errors of the fractional anisotropy map and trace map are obtained than those with the adaptive Wiener method, which in turn helps to produce more accurate DTIs.

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Authors and Affiliations

  1. Earth Science and Information Institute of Physics, Central South University, Changsha, 410083, China

    San-li Yi  (易三莉) & Hong-li Ling  (林红利)

  2. Life and Environment Institute, Guilin University of Electronic Technology, Guilin, 541004, China

    Zhen-cheng Chen  (陈真诚)

Authors
  1. San-li Yi  (易三莉)
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  2. Zhen-cheng Chen  (陈真诚)
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  3. Hong-li Ling  (林红利)
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Corresponding author

Correspondence to San-li Yi  (易三莉).

Additional information

Foundation item: Project(2009AA04Z214) supported by the National High Technology Research and Development Program of China; Project(07JJ6133) supported by the Natural Science Foundation of Hunan Province, China

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Yi, Sl., Chen, Zc. & Ling, Hl. Modified Wiener method in diffusion weighted image denoising. J. Cent. South Univ. Technol. 18, 2001–2008 (2011). https://doi.org/10.1007/s11771-011-0934-9

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  • DOI: https://doi.org/10.1007/s11771-011-0934-9

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