We report on the implementation and hardware platform of a real time Statistics-Based Positioning (SBP) method with depth of interaction processing for a positron emission tomography detector. The processing method works in conjunction with continuous miniature crystal element (cMiCE) detectors using a sensor on the entrance surface design. Our group previously reported on a Field Programmable Gate Array (FPGA) SBP implementation that provided a two dimensional (2D) detector positioning solution [1]. This new implementation extends that work to take advantage of three dimensional (3D) look up tables to provide a 3D positioning solution that improves intrinsic spatial resolution. Resolution is most improved along the edges of the crystal, an area where the 2D algorithm's performance suffers. The algorithm allows an intrinsic spatial resolution of 0.90 mm FWHM in X and Y and a resolution of 1.90 mm FWHM in Z (i.e., the depth of the crystal) based upon DETECT2000 simulation results that include the effects of Compton scatter in the crystal. A pipelined FPGA implementation is able to process events in excess of 220 K events per second, which is greater than the maximum expected coincidence rate for an individual detector. In contrast to all detectors being processed at a centralized host (as in the current system) a separate FPGA is available at each detector, thus dividing the computational load. A prototype design has been implemented and tested on an Altera Stratix II FPGA using a reduced word size due to memory limitations of our commercial prototyping board.Index Terms-Data acquisition, field programmable gate array, maximum likelihood estimation.

As FPGAs follow Moore's Law and increase in capacity and complexity, they are becoming more complex to use and are consuming increasing amounts of power. An interesting alternative for reconfigurable computing that is lower power and may be easier to program are Massively Parallel Processor Arrays (MPPAs). In this paper we investigate the Ambric AM2045, a commercial MPPA. To understand the differences between the architecture and computational models of MPPAs and FPGAs, we have implemented two pulse-processing algorithms used in Positron Emission Tomography (PET). The algorithms for event timing and event location were developed for FPGAs and then adapted to MPPAs. In this paper, we present the two implementations and discuss the main differences. Specifically, we show how the MPPA's lack of a real-time mode, their distributed memory structure, and object based programming model posed challenges for these algorithms.

We report on the implementation and hardware platform of a real time Statistics-Based Processing (SBP) method with depth of interaction processing for continuous miniature crystal element (cMiCE) detectors using a sensor on the entrance surface design. Our group previously reported on a Field Programmable Gate Array (FPGA) SBP implementation that provided a two dimensional (2D) solution of the detector's intrinsic spatial resolution. This new implementation extends that work to take advantage of three dimensional (3D) look up tables to provide a 3D positioning solution that improves intrinsic spatial resolution. Resolution is most improved along the edges of the crystal, an area where the 2D algorithm's performance suffers. The algorithm allows an intrinsic spatial resolution of ~0.90 mm FWHM in X and Y and a resolution of ~1.90 mm FWHM in Z (i.e., the depth of the crystal) based upon DETECT2000 simulation results that include the effects of Compton scatter in the crystal. A pipelined FPGA implementation is able to process events in excess of 220k events per second, which is greater than the maximum expected coincidence rate for an individual detector. In contrast to all detectors being processed at a centralized host, as in the current system, a separate FPGA is available at each detector, thus dividing the computational load. A prototype design has been implemented and tested using a reduced word size due to memory limitations of our commercial prototyping board.

We report on the implementation of an algorithm and hardware platform to allow real-time processing of the statistics-based positioning (SBP) method for continuous miniature crystal element (cMiCE) detectors. The SBP method allows an intrinsic spatial resolution of ~1.6 mm FWHM to be achieved using our cMiCE design. Previous SBP solutions have required a postprocessing procedure due to the computation and memory intensive nature of SBP. This new implementation takes advantage of a combination of algebraic simplifications, conversion to fixed-point math, and a hierarchal search technique to greatly accelerate the algorithm. For the presented seven stage, 127 × 127 bin LUT implementation, these algorithm improvements result in a reduction from >7 × 106 floating-point operations per event for an exhaustive search to < 5 × 103 integer operations per event. Simulations show nearly identical FWHM positioning resolution for this accelerated SBP solution, and positioning differences of <0.1 mm from the exhaustive search solution. A pipelined field programmable gate array (FPGA) implementation of this optimized algorithm is able to process events in excess of 250 K events per second, which is greater than the maximum expected coincidence rate for an individual detector. In contrast with all detectors being processed at a centralized host, as in the current system, a separate FPGA is available at each detector, thus dividing the computational load. These methods allow SBP results to be calculated in real-time and to be presented to the image generation components in real-time. A hardware implementation has been developed using a commercially available prototype board.