Comparison of different types of commercial filtered backprojection and ordered-subset expectation maximization SPECT reconstruction software.
The aim of this study was to compare the performance of filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM) reconstruction algorithms available in several types of commercial SPECT software.


METHODS
Numeric simulations of SPECT acquisitions of 2 phantoms were used: the National Electrical Manufacturers Association line phantom used for the assessment of SPECT resolution and a phantom with uniform, hot-rod, and cold-rod compartments. For FBP, no filtering and filtering of the projections with either a Butterworth filter (order 3 or 6) or a Hanning filter at various cutoff frequencies were considered. For OSEM, the number of subsets was 1, 4, 8, or 16, and the number of iterations was chosen to obtain a product number of iterations times the number of subsets equal to 16, 32, 48, or 64. The line phantom enabled us to obtain the reconstructed central, radial, and tangential full width at half maximum. The uniform compartment of the second phantom delivered the reconstructed mean pixel counts and SDs from which the coefficients of variation were calculated. Hot contrast and cold contrast were obtained from its rod compartments.


RESULTS
For FBP, the full width at half maximum, mean pixel count, coefficient of variation, and contrast were almost software independent. The only exceptions were a smaller (by 0.5 mm) full width at half maximum for one of the software types, higher mean pixel counts for 2 of the software types, and better contrast for 2 of the software types under some filtering conditions. For OSEM, the full width at half maximum differed by 0.1-2.5 mm with the different types of software but was almost independent of the number of subsets or iterations. There was a marked dependence of the mean pixel count on the type of software used, and there was a moderate dependence of the coefficient of variation. Contrast was almost software independent. The mean pixel count varied greatly with the number of iterations for 2 of the software types, and the coefficient of variation increased with the number of iterations for all types of software. The mean pixel count, coefficient of variation, and contrast were almost constant for a fixed product number of iterations times the number of subsets, whatever the number of subsets or iterations.


CONCLUSIONS
Most of the types of software were equivalent for FBP or OSEM reconstruction. However, a few differences were observed with some types of software and should be considered when they are used.
Seret
Alain
A
Imagerie Médicale Expérimentale, Université de Liège, Liège, Belgium. aseret@ulg.ac.be
Forthomme
Julien
J
D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016013:Likelihood Functions; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D012986:Software Validation; D015899:Tomography, Emission-Computed, Single-Photon / Q000295:instrumentation / Q000379:methods*