Accelerated SPECT reconstruction using OS-EM with only two projections per subset

In SPECT reconstruction, iterative Maximum Likelihood Expectation Maximization (ML-EM) estimation has a huge computational burden. The objective of this paper is to investigate how large a reduction in computation time can be obtained by using an algorithm acting on Ordered Subsets of projections (OS-EM). The authors validated OS-EM for a high number of subsets (which correlates with a high acceleration factor). Two phantoms, a cylinder with two cold spots and an ellipsoid with several hot spots and one cold spot were reconstructed from 120 noisy projections with the aid of a 1D (δ-like point source response), 2D (single slice response) and fully 3D PSF model. Signal-to-noise ratios (SNRs) and mean squared errors between phantoms and reconstructions as a function of contrast were calculated for OS-FM and ML-EM. Surprisingly, OS-EM outperforms ML-EM at high iteration numbers for the cylindrical phantom: OS-FM reconstructed images generally have a higher contrast at equivalent noise levels. For the ellipsoidal phantom the results of OS-EM are not superior, but certainly adequate, particularly so for the 3D PSF model, even when 60 subsets of opposing projections are used. In conclusion, the OS-EM algorithm using a high number of subsets is an extremely fast and reliable method to accelerate iterative SPECT reconstruction