title: Using deconvolution to improve PET spatial resolution in OSEM iterative reconstruction.
abstract: OBJECTIVE
  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.
authors.affiliation: Institute of Bioimaging and Molecular Physiology (IBFM)-CNR, University of Milano-Bicocca, San Raffaele Scientific Institute, Milan, Italy. giovanna.rizzo@ibfm.cnr.it
authors.forename: G
authors.initials: G
authors.lastname: Rizzo
authors.forename: I
authors.initials: I
authors.lastname: Castiglioni
authors.forename: G
authors.initials: G
authors.lastname: Russo
authors.forename: M G
authors.initials: MG
authors.lastname: Tana
authors.forename: F
authors.initials: F
authors.lastname: Dell'Acqua
authors.forename: M C
authors.initials: MC
authors.lastname: Gilardi
authors.forename: F
authors.initials: F
authors.lastname: Fazio
authors.forename: S
authors.initials: S
authors.lastname: Cerutti
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D010363:Pattern Recognition, Automated; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography; D011856:Radiographic Image Enhancement; D012815:Signal Processing, Computer-Assisted