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With continuous improvements in spatial resolution of positron emission tomography (PET) scanners, small patient movements during PET imaging become a significant source of resolution degradation. This work explores incorporation of motion information into expectation--maximization (EM) reconstruction algorithms. An important issue addressed is the existence of lines-of-response (LORs) corresponding to no actual pairs of detectors and their motion-induced "interaction" with the detectable LORs. An example of this is a scanner design with gaps existing in between the detector heads. It is shown that to properly account for such LORs in histogram-mode and list-mode EM reconstructions, in addition to motion correction of the events, the algorithms themselves must be modified. This modification is implemented by including motion-compensated sensitivity correction factors. We are able to demonstrate experimentally that the proposed approach resolves image artifacts that can appear when the conventional purely event-driven motion correction technique is used. An alternate image-space-based method for calculation of motion-compensated sensitivity factors is also derived, applicable in both histogram-mode and list-mode reconstruction tasks, which has the potential of being considerably faster in presence of frequent motion, especially in high-resolution tomographs. [ABSTRACT FROM AUTHOR]

The High Resolution Research Tomograph (HRRT) PET scanner is equipped with a moving Cs-137 transmission point source emitting 662 keV single photons. During post-injection transmission imaging 511 keV emission photons can be detected in the transmission window leading to gross underestimation of the reconstructed μ-value. Using cylindrical phantoms, methods to compensate for this emission contamination (EC) were investigated including histogram-based scaling and segmentation, while varying transmission window settings were used. Furthermore, the effects of subtracting a uniform or nonuniform EC estimation prior to transmission reconstruction were quantified. In conclusion, EC during HRRT transmission scans can Lead to gross underestimation of n-values, and the most accurate way to compensate for this is to combine nonuniform EC subtraction with transmission image segmentation. [ABSTRACT FROM AUTHOR]

This study empirically compares two approaches to parallel 3-D OSEM that differ as to whether calculations are assigned to nodes by projection number or by transaxial plane number. For projection space decomposition (PSD), the forward projection is completely parallel, but backprojection requires a slow image synchronization. For image space decomposition (ISD), the communication associated with forward projection can be overlapped with calculation, and the communication associated with backprojection is more efficient. To compare these methods, an implementation of 3-D OSEM for three PET scanners is developed that runs on an experimental 9-node, 18-processor cluster computer. For selected benchmarks, both methods exhibit speedups in excess of eight or nine nodes, and comparable performance for the tested range of cluster sizes. [ABSTRACT FROM AUTHOR]