Evaluation of a spline reconstruction technique: Comparison with FBP, MLEM and OSEM

An efficient, two-dimensional, analytic, Spline Reconstruction Technique (SRT) has been presented earlier in the literature. This technique involves the Hilbert transform of the sinogram which is approximated in terms of natural cubic splines. The aim of this study is to evaluate the SRT algorithm using Monte-Carlo simulated sinograms and real PET data, in comparison with three commonly used reconstruction algorithms: FBP, MLEM and OSEM. For the simulation studies, a digital Hoffman phantom, a NEMA-like and a Derenzo phantom were employed, and Monte Carlo methods were used for the simulation of the activity distribution in the source and the resulting generation of positron-electron annihilations. No noise, scatter and absorption conditions were assumed. The phantoms were generated with different image activities. The relevant modeled system was a single-ring tomograph with 234 scintillation crystals. Image grids with an image size of 128 × 128 pixels were employed. For the studies of real data, PET sinograms of an FDG injected mouse and a NEMA and Derenzo phantom were acquired from an ARGUS-CT small animal PET/CT system. Both the simulated and real sinograms were reconstructed using the SRT algorithm and the reconstructed images were compared to those of FBP, MLEM and OSEM. The contrast and SNR were calculated for the simulated NEMA-like and Hofmann phantom by drawing ROIs within the images. Our results indicate that SRT and FBP give reconstructed images of comparable quality with respect to the number of counts. Striking artifacts become worse at lower total counts for both methods. SRT reconstructed images exhibit higher SNR in comparison with FBP and, in some cases, in comparison with MLEM and OSEM. SRT reconstructed images exhibit higher contrast over FBP but not over MLEM and OSEM. The reconstruction time for SRT was about 20 sec per slice, hence SRT is faster than MLEM and OSEM (for high activity images), but slower than FBP. In conclusion, SRT is a l- - inear algorithm which can serve as a good alternative to FBP, providing images with higher contrast and SNR values. Furthermore, it has the crucial advantage that it can accommodate complicated detector geometries.