Parametric images can help investigate disease mechanisms and vital functions. To estimate parametric images, it is necessary to obtain the tissue time activity curves (tTACs), which express temporal changes of tracer activity in human tissue. In general, the tTACs are calculated from each voxel's value of the time sequential PET images estimated from dynamic PET data. Recently, spatio-temporal PET reconstruction methods have been proposed in order to take into account the temporal correlation within each tTAC. Such spatio-temporal algorithms are generally quite computationally intensive. On the other hand, typical algorithms such as the preconditioned conjugate gradient (PCG) method still does not provide good accuracy in estimation. To overcome these problems, we propose a new spatio-temporal reconstruction method based on the dynamic row-action maximum-likelihood algorithm (DRAMA). As the original algorithm does, the proposed method takes into account the noise propagation, but it achieves much faster convergence. Performance of the method is evaluated with digital phantom simulations and it is shown that the proposed method requires only a few reconstruction processes, thereby remarkably reducing the computational cost required to estimate the tTACs. The results also show that the tTACs and parametric images from the proposed method have better accuracy.

We consider delivering interactive dramas. A viewer interacts with a contents provider by answering multiple-choice questions and the answers to these questions influence the plot of delivered story. All possible plots can be represented by a directed graph such that every plot corresponds to some path of the graph. A delivery should be controlled according to the directed graph such that each viewer's history of answered choices forms a path of the graph. On the other hand, because some character of a viewer is known to a contents provider from his history of choices, a viewer tries to prevent even a contents provider from linking choices made by him. In this paper, we introduce unlinkable delivery for an interactive drama and propose such a delivery system for interactive dramas that viewer's choices are unlinkable and delivery is controlled according to the directed graph.