The multi-voltage threshold (MVT) method, proposed by us, is a method for digitizing a PET event pulse by sampling with respect to certain reference voltages. Previously, we have implemented this method by using discrete voltage comparators together with discrete time-to-digital converters (TDCs) or TDCs implemented on a field-programmable-gate-array (FPGA), and shown that the method is useful for developing PET detectors capable of time-of-flight (TOF) measurement. In this paper, we investigate an FPGA-only implementation in which the differential I/Os of the FPGA operating in the low-voltage-differential-signaling (LVDS) receiver mode are configured to provide the function of the voltage comparators. Using an Altera Cyclone II Family FPGA (EP2C70F896C7), we built two MVT digitizing channels, each of which contains four comparators to yield eight samples for each event pulse. We describe the design, implementation and calibration of this FPGA-only MVT digitizer and report its performance properties. By connecting the channels to SensL's silicon photomultipliers (SiPMs) FM30035 coupled to 2 ×2×10 mm ³ LYSO crystals, we measured an energy resolution of ~16% (at 511 keV) and a coincidence resolving time (CRT) of ~ 500 ps (FWHM). These resolutions are promising for developing PET and TOF PET detectors. On the other hand, based on digitized waveforms of pulses generated by the same SiPMs and LYSOs acquired by using a 50 giga-sample-per-second (Gsps) digital oscilloscope (Tektronics DPO71604B), we measured an energy resolution of ~9% and a CRT of ~390 ps. The comparison suggests that our current implementation of the FPGA-only MVT digitizer contributes an ~13% energy resolution and ~310 ps CRT.

In this paper, we propose a new technique for positron emission tomography (PET) pulse processing that has the potential to overcome design limitations in PET arising from the need to use fast, high-cost analog-to-digital converters (ADCs). In this technique, we consider the voltage pulse derived from the charge pulse generated by a scintillator/photomultiplier tube (PMT) detector upon a detection event and model the voltage pulse by a fast, linearly rising edge followed by a slower exponential decay. Based on this model, we show that the basic parameters of the voltage pulse that are relevant for PET event detection can be determined from a trigger time and four time intervals measured on the pulse. We also discuss an electronic implementation in which the required measurements can be obtained by using clocks, comparators, and registers, thereby eliminating the use of ADCs and constant fraction discriminators in PET front-end electronics. We conduct computer simulation studies to evaluate the performance of the proposed technique and our results are promising. When used with Cerium Doped Lutetium Oxyorthosilicate (LSO)/PMT, the proposed technique can generate accurate results for the photon energy, the event time, and the decay-time constant. In addition, it can support an energy resolution of about 30% and a coincidence window of about 10 ns. On the other hand, in its present form the proposed technique is not suitable for use with BGO/PMT due to its low light yield.

We investigate the potentials of digitally sampling scintillation pulses techniques for positron emission tomography (PET) in this paper, focusing on the determination of the event time. We have built, and continue building, a digital library of PET event waveforms generated with various combinations of photo-detectors and scintillator materials, with various crystal sizes. Events in this digital library are obtained at a high sampling of 20 GSps (Giga-samples per second) so that their waveforms are recorded with high accuracy. To explore the potential advantages of digitally sampling scintillation pulses, we employ a dataset in the above-mentioned library to evaluate two methods for digitizing the event pulses and linear interpolation techniques to analyze the resulting digital samples. Our results show that the two digitization methods that we studied can yield a coincidence timing resolution of about 300 ps FWHM when applied to events generated by a pair of LSO + PMT detector units. This timing resolution is comparable with that is achieved by the same detector pair with a constant fraction discriminator (CFD). As a benchmark, regular-time sampling (RTS) method, usually implemented with very fast traditional analog-to-digital converters (ADCs) for digitizing scintillation pulses, is not feasible for a multi-channel system like a PET system. Digitizing scintillation pulses with multi-voltage threshold (MVT) method could be implemented at a reasonable cost for a PET system. With digitized PET event samples, various digital signal processing (DSP) techniques can be implemented to determine event arrival time. Our results have therefore demonstrated the promising potentials of digitally sampling scintillation pulses techniques in PET imaging.

Interest remains in reconstruction-algorithm research and development for possible improvement of image quality in current PET imaging and for enabling innovative PET systems to enhance existing, and facilitate new, preclinical and clinical applications. Optimization-based image reconstruction has been demonstrated in recent years of potential utility for CT imaging applications. In this work, we investigate tailoring the optimization-based techniques to image reconstruction for PET systems with standard and non-standard scan configurations. Specifically, given an image-total-variation (TV) constraint, we investigated how the selection of different data divergences and associated parameters impacts the optimization-based reconstruction of PET images. The reconstruction robustness was explored also with respect to different data conditions and activity up-takes of practical relevance. A study was conducted particularly for image reconstruction from data collected by use of a PET configuration with sparsely populated detectors. Overall, the study demonstrates the robustness of the TV-constrained, optimization-based reconstruction for considerably different data conditions in PET imaging, as well as its potential to enable PET configurations with reduced numbers of detectors. Insights gained in the study may be exploited for developing algorithms for PET-image reconstruction and for enabling PET-configuration design of practical usefulness in preclinical and clinical applications.