An Investigation of Stochastic Variance Reduction Algorithms for 3D
Penalised PET Image Reconstruction
AbstractApplication of stochastic variance reduction algorithms to iterative PET
reconstruction. We investigated the SAGA and SVRG algorithms for non-TOF
PET image reconstruction. Both similated data and a patient data sets
were used in the analysis. We found that the stochastic algorithms can
improve convergence rate and eliminate behaviour, commonly know as limit
cycle behaviour, from PET reconstruction within 5 epochs.