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Tetrault, M. A., Oliver, J. F., Bergeron, M., Lecomte, R., & Fontaine, R. (2010). Real Time Coincidence Detection Engine for High Count Rate Timestamp Based PET. IEEE Trans. Nucl. Sci., 57(1), 117–124.
Abstract: Coincidence engines follow two main implementation flows: timestamp based systems and AND-gate based systems. The latter have been more widespread in recent years because of its lower cost and high efficiency. However, they are highly dependent on the selected electronic components, they have limited flexibility once assembled and they are customized to fit a specific scanner's geometry. Timestamp based systems are gathering more attention lately, especially with high channel count fully digital systems. These new systems must however cope with important singles count rates. One option is to record every detected event and postpone coincidence detection offline. For daily use systems, a real time engine is preferable because it dramatically reduces data volume and hence image preprocessing time and raw data management. This paper presents the timestamp based coincidence engine for the LabPET(TM), a small animal PET scanner with up to 4608 individual readout avalanche photodiode channels. The engine can handle up to 100 million single events per second and has extensive flexibility because it resides in programmable logic devices. It can be adapted for any detector geometry or channel count, can be ported to newer, faster programmable devices and can have extra modules added to take advantage of scanner-specific features. Finally, the user can select between full processing mode for imaging protocols and minimum processing mode to study different approaches for coincidence detection with offline software.
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Real, D., Calvo, D., Diaz, A., Alves Garre, S., Carretero, V., Sanchez Losa, A., et al. (2023). An Ultra-Narrow Time Optical Pulse Emitter Based on a Laser: UNTOPEL. IEEE Trans. Nucl. Sci., 70(10), 2364–2372.
Abstract: Light sources that emit repetitive subnanosecond pulses are used in neutrino telescopes for time calibration. Optical pulses with an ultra-narrow (subnanosecond) width can replicate the light produced by neutrino interactions, and are an important calibration and test element. By measuring the time-of-flight of the light, it is possible to provide a relative time calibration for all the detector photomultipliers. This work presents the ultra-narrow time optical pulse emitter based on a laser (UNTOPEL), an instrument emitting ultra-short laser optical pulses with a duration of 500 ps, energies per pulse of four microjoules at a wavelength of 532 nm, and a timing precision of 400 ps. The UNTOPEL pulse intensity can be fine-tuned, which is a novelty and a significant advantage in those applications that need to illuminate light detectors located at different distances with the same light intensity. The UNTOPEL pulse intensity can be controlled remotely, allowing for its use in operating conditions where physical access is impossible or difficult. Moreover, it is easy to operate and can be easily controlled through an inter-integrated circuit bus. The UNTOPEL is a sound instrument used when subnanosecond pulses and variable energy emissions are needed.
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Oliver, J. F., Fuster-Garcia, E., Cabello, J., Tortajada, S., & Rafecas, M. (2013). Application of Artificial Neural Network for Reducing Random Coincidences in PET. IEEE Trans. Nucl. Sci., 60(5), 3399–3409.
Abstract: Positron Emission Tomography (PET) is based on the detection in coincidence of the two photons created in a positron annihilation. In conventional PET, this coincidence identification is usually carried out through a coincidence electronic unit. An accidental coincidence occurs when two photons arising from different annihilations are classified as a coincidence. Accidental coincidences are one of the main sources of image degradation in PET. Some novel systems allow coincidences to be selected post-acquisition in software, or in real time through a digital coincidence engine in an FPGA. These approaches provide the user with extra flexibility in the sorting process and allow the application of alternative coincidence sorting procedures. In this work a novel sorting procedure based on Artificial Neural Network (ANN) techniques has been developed. It has been compared to a conventional coincidence sorting algorithm based on a time coincidence window. The data have been obtained from Monte-Carlo simulations. A small animal PET scanner has been implemented to this end. The efficiency (the ratio of correct identifications) can be selected for both methods. In one case by changing the actual value of the coincidence window used, and in the other by changing a threshold at the output of the neural network. At matched efficiencies, the ANN-based method always produces a sorted output with a smaller random fraction. In addition, two differential trends are found: the conventional method presents a maximum achievable efficiency, while the ANN-based method is able to increase the efficiency up to unity, the ideal value, at the cost of increasing the random fraction. Images reconstructed using ANN sorted data (no compensation for randoms) present better contrast, and those image features which are more affected by randoms are enhanced. For the image quality phantom used in the paper, the ANN method decreases the spill-over ratio by a factor of 18%.
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Nguyen, C. V., Gillam, J. E., Brown, J. M. C., Martin, D. V., Nikulin, D. A., & Dimmock, M. R. (2011). Towards Optimal Collimator Design for the PEDRO Hybrid Imaging System. IEEE Trans. Nucl. Sci., 58(3), 639–650.
Abstract: The Pixelated Emission Detector for RadiOisotopes (PEDRO) is a hybrid imaging system designed for the measurement of single photon emission from small animal models. The proof-of-principle device consists of a Compton-camera situated behind a mechanical collimator and is intended to provide optimal detection characteristics over a broad spectral range, from 30 to 511 keV. An automated routine has been developed for the optimization of large-area slits in the outer regions of a collimator which has a central region allocated for pinholes. The optimization was tested with a GEANT4 model of the experimental prototype. The data were blurred with the expected position and energy resolution parameters and a Bayesian interaction ordering algorithm was applied. Images were reconstructed using cone back-projection. The results show that the optimization technique allows the large-area slits to both sample fully and extend the primary field of view (FoV) determined by the pinholes. The slits were found to provide truncation of the back-projected cones of response and also an increase in the success rate of the interaction ordering algorithm. These factors resulted in an increase in the contrast and signal-to-noise ratio of the reconstructed image estimates. Of the two configurations tested, the cylindrical geometry outperformed the square geometry, primarily because of a decrease in artifacts. This was due to isotropic modulation of the cone surfaces, that can be achieved with a circular shape. Also, the cylindrical geometry provided increased sampling of the FoV due to more optimal positioning of the slits. The use of the cylindrical collimator and application of the transmission function in the reconstruction was found to improve the resolution of the system by a factor of 20, as compared to the uncollimated Compton camera. Although this system is designed for small animal imaging, the technique can be applied to any application of single photon imaging.
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Miñano, M. (2011). Radiation Hard Silicon Strips Detectors for the SLHC. IEEE Trans. Nucl. Sci., 58(3), 1135–1140.
Abstract: While the Large Hadron Collider (LHC) began taking data in 2009, scenarios for a machine upgrade to achieve a much higher luminosity are being developed. In the current planning, it is foreseen to increase the luminosity of the LHC at CERN around 2018. As radiation damage scales with integrated luminosity, the particle physics experiments will need to be equipped with a new generation of radiation hard detectors. This article reports on the status of the R&D projects on radiation hard silicon strips detectors for particle physics, linked to the Large Hadron Collider Upgrade, super-LHC (sLHC) of the ATLAS microstrip detector. The primary focus of this report is on measuring the radiation hardness of the silicon materials and the detectors under study. This involves designing silicon detectors, irradiating them to the sLHC radiation levels and studying their performance as particle detectors. The most promising silicon detector for the different radiation levels in the different regions of the ATLAS microstrip detector will be presented. Important challenges related to engineering layout, powering, cooling and reading out a very large strip detector are presented. Ideas on possible schemes for the layout and support mechanics will be shown.
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