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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-07

AUTHORS

N. Boussion, C. Cheze Le Rest, M. Hatt, D. Visvikis

ABSTRACT

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-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. 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. More... »

PAGES

1064-1075

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00259-009-1065-5

DOI

http://dx.doi.org/10.1007/s00259-009-1065-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1052639217

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19224209


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