Quantitative analysis of a reconstruction method for fully three-dimensional PET

The major advantage of positron emission tomography (PET) using large area planar detectors over scintillator-based commercial ring systems is the potentially larger (by a factor of two or three) axial field-of-view (FOV). However, to achieve the space invariance of the point spread function necessary for Fourier filtering a polar angle rejection criterion is applied to the data during backprojection resulting in a trade-off between FOV size and sensitivity. A new algorithm due to Defrise and co-workers developed for list-mode data overcomes this problem with a solution involving the division of the image into several subregions. A comparison between the existing backprojection-then-filter algorithm and the new method (with three subregions) has been made using both simulated and real data collected from the MUP-PET positron camera. Signal-to-noise analysis reveals that improvements of up to a factor of 1.4 are possible resulting from an increased data usage of up to a factor of 2.5 depending on the axial extent of the imaged object. Quantitation is also improved.