Noise models for sinusoidal trajectories composing sinogram data in positron emission tomography

Projection data in Positron Emission Tomography (PET) are acquired as a number of photon counts from different observation angles. Positron decay is a random phenomenon that causes undesirably high variations in measured sinogram appearing as noise. Filtering of the raw data in a stackgram domain is a new technique capable of producing the reliable estimates of underlying activity. However, to facilitate accurate denoising procedure of the emission data, signals constituting the stackgram should be properly modelled. In this study, the choice of appropriate noise model for them is considered. We will demonstrate that the general two-parameter distributions can be employed to properly characterize the source of errors coming from the data measurement process and from the decay process of the positron emitting tracer.