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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 tomagraphs. Index Terms--Expectation-maximization (EM) algorithm, histogram-mode, list-mode, motion compensation, positron emission tomography (PET) reconstruction.

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 [micro]-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 [micro]-values, and the most accurate way to compensate for this is to combine nonuniform EC subtraction with transmission image segmentation. Index Terms--Emission contamination, image reconstruction, High Resolution Research Tomograph (HRRT), PET, transmission.

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. Index Terms--Biomedical image processing, image reconstruction, parallel algorithms, parallel processing, positron emission tomography.

The high resolution research tomograph (HRRT) is a 3-D PET scanner designed for human brain and small animal imaging. The HRRT consists of eight panel detector heads that are separated by gaps of 17 mm resulting in gaps in the sinogram. Furthermore, gaps can result from detector-block failure. To prevent artifacts in the reconstruction when using Fourier rebinning (FORE), filling the data gaps is required. The purpose of this study was to evaluate the accuracy of three gap filling methods: a) bilinear interpolation of sinogram data; b) a model-based method in which an intermediate volume is reconstructed [2-D ordered subsets expectation maximization (2-D OSEM)] based on direct planes only, after which this image is forward projected to fill the gaps; c) an improved model-based method in which gaps are first filled using interpolation, then reconstructed using FORE + 2-D OSEM and forward projected. The improved model-based method outperforms interpolation, but requires more computation time. Index Terms--HRRT, image reconstruction, missing data, PET, sinograms.

A daily quality check (DQC) plays an important role for clinical medical systems like a positron emission tomograph (PET). To guarantee image quality a constant monitoring of the scanner integrity is essential. On present PET scanners, the built-in transmission sources are being used for the measurement of a uniform blank scan and the computation of detector-block efficiencies. These efficiencies can be compared to reference data and deviations indicate changes of the scanner condition. On the high-resolution research tomograph (ECAT HRRT) the design of the transmission source makes this method impractical. For that reason we investigated the use of the natural background radioactivity from the new scintillator material LSO as a uniform source. A procedure was developed to measure detector-block sensitivities and energy spectra directly. An initial quality check (QC) scan is the basis for comparison of daily scans, so that gain shifts of photomultipliers and specific hardware defects can be detected. With an improved list mode based data acquisition it was possible to reduce the acquisition time to around 3 h despite the low LSO count rate, so that this routine is as practical as previous procedures in clinical routine. Index Terms--Daily quality check (DQC), lutetium-oxy-orthosilicate (LSO), positron emission tomography (PET).

We describe the electronics for a high-performance positron emission mammography (PEM) camera. It is based on the electronics for a human brain positron emission tomography (PET) camera (the Siemens/CTI HRRT), modified to use a detector module that incorporates a photodiode (PD) array. An application-specified integrated circuit (ASIC) services the photodetector (PD) array, amplifying its signal and identifying the crystal of interaction. Another ASIC services the photomultiplier tube (PMT), measuring its output and providing a timing signal. Field-programmable gate arrays (FPGAs) and lookup RAMs are used to apply crystal-by-crystal correction factors and measure the energy deposit and the interaction depth (based on the PD/PMT ratio). Additional FPGAs provide event multiplexing, derandomization, coincidence detection, and real-time rebinning. Embedded PC/104 microprocessors provide communication, real-time control, and configure the system. Extensive use of FPGAs make the overall design extremely flexible, allowing many different functions (or design modifications) to be realized without hardware changes. Incorporation of extensive onboard diagnostics, implemented in the FPGAs, is required by the very high level of integration and density achieved by this system.

A high resolution PET scanner requiring processing electronics for 936 block technology channels and just under sixty-thousand crystal elements has been developed. With the advances in flexibility, number of gates, lower costs and speed of Field Programmable Gate Arrays (FPGA), an FPGA implementation of the front-end processing electronics was chosen over the traditional discrete logic or Application Specific Integrated Circuit (ASIC) [1]. The FPGA architecture reduced the development time and risks compared to a mask-based ASIC architecture while keeping costs and electronics packing density comparable. The extensive use FPGAs enables much faster circuit realization and a very efficient logic utilization by allowing re-configuration of the electronics functionality to support system setup, self-diagnostics, and several calibration modes for detector setup. Logic realized within the FPGAs performs the crystal selection, energy qualification, time correction, depth of interaction determination, and event counting functions. Since the FPGAs are in-circuit re-configurable (ICR), the functionality of the electronics is easily modified to support the different modes of operation. Thus the development time is reduced as well as the amount of electronics required, saving board area, power consumption and costs.