Purpose: 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-R chardson 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. Results: 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. Conclusion: The appropriate combination of deconvolution and wavelet-based denoising is an efficient method for reducing PVEs in emission tomography. © 2009 Springer-Verlag.
CITATION STYLE
Boussion, N., Cheze Le Rest, C., Hatt, M., & Visvikis, D. (2009). Incorporation of wavelet-based denoising in iterative deconvolution for partial volume correction in whole-body PET imaging. European Journal of Nuclear Medicine and Molecular Imaging, 36(7), 1064–1075. https://doi.org/10.1007/s00259-009-1065-5
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