Using deconvolution to improve PET spatial resolution in OSEM iterative reconstruction

Institute of Bioimaging and Molecular Physiology (IBFM)-CNR, University of Milano-Bicocca, San Raffaele Scientific Institute, Milan, Italy.
Methods of Information in Medicine (Impact Factor: 2.25). 02/2007; 46(2):231-5.
Source: PubMed


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.
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.
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.
Application of this approach to both simulated and acquired data suggests its efficacy in obtaining PET images of enhanced quality.

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Available from: Giovanna Rizzo, Jul 02, 2014
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    • "Finally, a recent work of Rahmim et al. (2008) strictly applied the idea of equation (4), putting the positron range correction in image space and the other corrections in sinogram space. Other works and applications on clinical data include Rahmim, Cheng and Sossi (2005), Rizzo et al. (2007), Varrone et al. (2009), Mourik et al. (2010) and Hoetjes et al. (2010). "
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