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Respiratory motion is a major factor that affects the quality of PET images of the thoracic area. The diaphragm moves about 15–20 mm due to respiratory motion, which substantially degrades the effective spatial resolution of PET. In this paper, a gated acquisition method is used to correct the motion effects. In this method, an improved demons algorithm is proposed to align the gated images. The experimental results show that the quality of PET images is significantly improved when using our improved method and the proposed method has a faster convergence rate than the original demons algorithm.

In fully three-dimensional (3D) positron emission tomography (PET) imaging, the scatter fraction (SF) is about 40%-60%, which may degrade the imaging quality severely. Scatter correction is important for high quality image reconstruction. Model-based scatter correction has been proved to be accurate and available in clinical PET. However, it does not correct the scatter from out of the field of view (OFOV) and multiple scatters. In this study, we demonstrate the radial and axial distribution of scatters from OFOV when the source is located in different radial positions. In order to apply the above conclusions to different PET systems, we characterize the scatters from OFOV as a function of the ratio of the scanner diameter to the length of the axial field of view (AFOV) by modeling several typical whole-body and micro PET systems. The proportions of true events (S0–0), single scatter of one photon (S1–0), single scatter of both photons (S1–1), double scatter of one photon (S2–0) and multiple scatter (Sm) are also calculated and compared. Here the 3D-PET Monte Carlo simulations are performed with the Geant4 Application for Tomography Emission (GATE). In summary, the scatters from OFOV tend to be recorded on the lines of response (LOR) far away from the source. They have a much more serious impact on whole-body PET than micro PET depending on the ratio of scanner diameter to the length of AFOV. In whole-body PET, twice scatters including single scatter of both photons (S1–1) and double scatter of one photon (S2–0) add up to about 12% so that twice scatter correction must be taken into account to acquire a high quality reconstruction image.

A point spread function (PSF) for the blurring component in positron emission tomography (PET) is studied. The PSF matrix is derived from the single photon incidence response function. A statistical iterative reconstruction (IR) method based on the system matrix containing the PSF is developed. More specifically, the gamma photon incidence upon a crystal array is simulated by Monte Carlo (MC) simulation, and then the single photon incidence response functions are calculated. Subsequently, the single photon incidence response functions are used to compute the coincidence blurring factor according to the physical process of PET coincidence detection. Through weighting the ordinary system matrix response by the coincidence blurring factors, the IR system matrix containing the PSF is finally established. By using this system matrix, the image is reconstructed by an ordered subset expectation maximization (OSEM) algorithm. The experimental results show that the proposed system matrix can substantially improve the image radial resolution, contrast, and noise property. Furthermore, the simulated single gamma-ray incidence response function depends only on the crystal configuration, so the method could be extended to any PET scanner with the same detector crystal configuration.