Incorporation of wavelet-based denoising in iterative deconvolution for partial volume correction in whole-body PET imaging

  • N. BoussionEmail author
  • C. Cheze Le Rest
  • M. Hatt
  • D. Visvikis
Original Article



Partial volume effects (PVEs) are consequences of the limited resolution of emission tomography. The aim of the present study was to compare two new voxel-wise PVE correction algorithms based on deconvolution and wavelet-based denoising.

Materials and methods

Deconvolution was performed using the Lucy-Richardson and the Van-Cittert algorithms. Both of these methods were tested using simulated and real FDG PET images. Wavelet-based denoising was incorporated into the process in order to eliminate the noise observed in classical deconvolution methods.


Both deconvolution approaches led to significant intensity recovery, but the Van-Cittert algorithm provided images of inferior qualitative appearance. Furthermore, this method added massive levels of noise, even with the associated use of wavelet-denoising. On the other hand, the Lucy-Richardson algorithm combined with the same denoising process gave the best compromise between intensity recovery, noise attenuation and qualitative aspect of the images.


The appropriate combination of deconvolution and wavelet-based denoising is an efficient method for reducing PVEs in emission tomography.


FDG-PET Image processing Partial volume correction Whole-body PET 


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • N. Boussion
    • 1
    Email author
  • C. Cheze Le Rest
    • 1
  • M. Hatt
    • 1
  • D. Visvikis
    • 1
  1. 1.INSERM, U650, Laboratoire de Traitement de l’Information Médicale (LaTIM) CHU MORVANBrestFrance

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