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Information Sciences and Systems 2015 pp 275–284Cite as

Brain MR Image Denoising for Rician Noise Using Intrinsic Geometrical Information

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 363))

Abstract

A new image denoising algorithm based on nonsubsampled contourlet transform is presented. Magnetic Resonance (MR) images corrupted by Rician noise are transformed into multi-scale and multi-directional contour information, where a nonlinear mapping function is used to modify the contour coefficients at each level. The denoising is achieved by improving edge sharpness and inhibiting the background noise. Experiments show the proposed algorithm preserves the intrinsic geometrical information of the noised MR image and can be effectively applied to T1-, T2-, and PD-weighted MR images without any parameter tuning under diverse noise levels.

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Notes

  1. 1.

    The nonsubsampled contourlet toolbox used in this paper can be downloaded at http://www.mathworks.com/matlabcentral/fileexchange/10049-nonsubsampled-contourlet-toolbox.

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Author information

Authors and Affiliations

  1. Queen Mary University of London, London, UK

    Hamit Soyel & Peter W. McOwan

  2. Cyprus International University, Lefkoşa, Mersin Turkey

    Kamil Yurtkan

  3. Eastern Mediterranean University, Gazimağusa, Mersin Turkey

    Hasan Demirel

Authors
  1. Hamit Soyel
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  2. Kamil Yurtkan
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  3. Hasan Demirel
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  4. Peter W. McOwan
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Corresponding author

Correspondence to Hamit Soyel .

Editor information

Editors and Affiliations

  1. Department of Electrical, Imperial College, London, United Kingdom

    Omer H. Abdelrahman

  2. Department of Electrical and Electronic Engineering, Imperial College, London, United Kingdom

    Erol Gelenbe

  3. Department of Electrical and Electronic Engineering, Imperial College, London, United Kingdom

    Gokce Gorbil

  4. Department of Engineering Technology, University of Houston, Houston, Texas, USA

    Ricardo Lent

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© 2016 Springer International Publishing Switzerland

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Soyel, H., Yurtkan, K., Demirel, H., McOwan, P.W. (2016). Brain MR Image Denoising for Rician Noise Using Intrinsic Geometrical Information. In: Abdelrahman, O., Gelenbe, E., Gorbil, G., Lent, R. (eds) Information Sciences and Systems 2015. Lecture Notes in Electrical Engineering, vol 363. Springer, Cham. https://doi.org/10.1007/978-3-319-22635-4_25

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  • DOI: https://doi.org/10.1007/978-3-319-22635-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22634-7

  • Online ISBN: 978-3-319-22635-4

  • eBook Packages: EngineeringEngineering (R0)

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