Generalized matrix inverse reconstruction for SPECT using a weighted singular value spectrum

A method of weighting the singular value spectrum for SPECT image reconstruction with generalized matrix inverses (GMIs) has been developed. At each source voxel, spectral weights are computed to minimize the misfit of the resolution kernel with a delta function, subject to a constraint on the variance of the reconstructed source voxel activity. The method was applied to a Monte Carlo simulated Tc-99m myocardial perfusion study and a Tc-99m myocardial perfusion phantom study acquired on a clinical scanner. GMI reconstructions using weighted and truncated spectra were compared. Resolution kernels for a weighted spectrum are narrower and have smaller sidelobes than kernels for a truncated spectrum. As a result, the quality of reconstructed SPECT images is improved and the simulated myocardial wall thickness is better estimated with the use of a weighted spectrum. The use of a weighted singular value spectrum is an important tool for obtaining more localized source activity estimates for GMI reconstruction