Modeling dynamic PET-SPECT studies in the wavelet domain

This work develops a theoretical framework and corresponding algorithms for the modeling of dynamic PET-SPECT studies both in time and space. The problem of estimating the spatial dimension is solved by applying the w avelet transform to each scan of the dynamic sequence and then performing t he kinetic modeling and statistical analysis in the wavelet domain. On reco nstruction through the inverse wavelet transform, one obtains parametric im ages that are consistent estimates of the spatial patterns of the kinetic p arameter of interest. The theoretical setup allows the use of linear techni ques currently used in PET-SPECT for kinetic analysis. The method is applie d to artificial and real data sets. The application to dynamic PET-SPECT st udies was performed both for validation purposes, when the spatial patterns are known, and for illustration of the advantages offered by the technique in case of tracers with an unknown pattern of distribution.