Simulation study on the performance of time-over-threshold based positioning in monolithic PET detectors

The vast majority of PET detectors in the field today is based on pixelated scintillators. Yet, the resolution of this type of detector is limited by the pixel size. To overcome this limitation one can use monolithic detectors. However, this detector architecture demands specific and high-speed detector readout of the photodetector array. A commonly used approach is to integrate the current pulses generated by every pixel but such circuitry quickly becomes bulky, power consuming and expensive. The objective of this work is to investigate a novel readout and event positioning scheme for monolithic PET detectors, based on Time-over-Threshold (ToT). In this case, we measure the time that the pulse is above a certain threshold through a comparator. The pulse widths are used for event positioning using a mean nearest neighbour approach (mNNToT). For energy determination one integrating multiplexed channel is foreseen. We evaluate the positioning accuracy and uniformity of such a ToT detector by means of Monte Carlo simulations. The impact of the threshold value is investigated and the results are compared to a detector using mean nearest neighbour with pulse-integration (mNNint), which has already proven to allow sub-mm resolution. We show minimal degradation in spatial resolution and bias performance compared to mNNint. The highest threshold results in the worst resolution performance but degradation remains below 0.1 mm. Bias is largely constant over different thresholds for mNNToT and close to identical to mNNint. Furthermore we show that Time-over-Threshold performs well in terms of detector uniformity and that scattered photons can be positioned inside the crystal with high accuracy. We conclude from this work that ToT is a valuable alternative to pulse-integration for monolithic PET detectors. This novel approach has an impact on PET detector development since it has the advantage of lower power consumption, compactness and inherent amplitude-to-time conversion.

Improving The Subdivision Accuracy of Photoelectric Encoder Using Particle Swarm Optimization Algorithm

To improve the subdivision accuracy of a photoelectric encoder and reduce the effects of sinusoidal errors in the signals on the measurement accuracy of the system, we designed an optoelectronic chip to receive grating moiré fringe signals. An amplifier circuit with a hierarchical pipelined architecture was designed, and the photodetector array was matched with the code disk before processing the received signals. Thereafter, a quantitative analysis was performed on the sinusoidal errors in the signals. From the analysis results, a sinusoidal error compensation method based on the particle swarm optimization (PSO) algorithm was developed, and a subdivision error compensation model was established to correct the errors in the signals. Finally, a fast solution for the PSO algorithm was implemented on a field-programmable gate array, and a grating test platform was built for experimental verifications. The results showed that the peak-to-peak subdivision error of the encoder’s photoelectric signal decreased by approximately 60% from 2.98ʺ to 1.13ʺ. Therefore, the scheme proposed in this paper is expected to significantly improve the measurement accuracies of photoelectric encoders.