A statistical approach to transmission image reconstruction from ring source calibration measurements in PET

The problem of reconstructing a transmission attenuation image is addressed. The estimation procedure is based on a Bayesian formulation incorporating a Poisson likelihood model that includes scatter for the transmission data and a Markov random field prior. The results obtained using this approach result in improved accuracy in computing the ACFs (attenuation correction factors). A transmission image is also useful for reconstructing anatomical landmarks for use in cross-modality registration. A third advantage of reconstruction of the transmission image is that, if the patient moves between the transmission and one or more emission scans, the reconstructed transmission image can be used to generate ACFs for any new position. Several candidate optimization techniques are investigated, and the quantitative accuracy of the reconstructed images is evaluated