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G. Rizzo, I. Castiglioni, G. Russo, M. G. Tana, F. DellAcqua, M. C. Gilardi, F. Fazio, S. Cerutti
Using Deconvolution to Improve PET Spatial Resolution in OSEM Iterative Reconstruction
Keywords: Deconvolution, OSEM reconstruction, PET spatial resolution recovery
OBJECTIVES: A novel approach to the PET image reconstruction is presented, based on the inclusion of image deconvolution during conventional OSEM reconstruction. Deconvolution is here used to provide a recovered PET image to be included as a priori information to guide OSEM toward an improved solution. METHODS: Deconvolution was implemented using the Lucy-Richardson (LR) algorithm: Two different deconvolution schemes were tested, modifying the conventional OSEM iterative formulation: 1) We built a regularizing penalty function on the recovered PET image obtained by deconvolution and included it in the OSEM iteration. 2) After each conventional global OSEM iteration, we deconvolved the resulting PET image and used this recovered version as the initialization image for the next OSEM iteration. Tests were performed on both simulated and acquired data. RESULTS: Compared to the conventional OSEM, both these strategies, applied to simulated and acquired data, showed an improvement in image spatial resolution with better behavior in the second case. In this way, small lesions, present on data, could be better discriminated in terms of contrast. CONCLUSIONS: Application of this approach to both simulated and acquired data suggests its efficacy in obtaining PET images of enhanced quality.
Methods of Information in Medicine, Schattauer
Print ISSN: 0026-1270
Volume: 46, 01/2007
Pages: 231 - 235