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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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DEPFET collaboration(Alonso, O. et al), Boronat, M., Esperante-Pereira, D., Fuster, J., Garcia, I. G., Lacasta, C., et al. (2013). DEPFET Active Pixel Detectors for a Future Linear e(+)e(-) Collider. IEEE Trans. Nucl. Sci., 60(2), 1457–1465.
Abstract: The DEPFET collaboration develops highly granular, ultra-transparent active pixel detectors for high-performance vertex reconstruction at future collider experiments. The characterization of detector prototypes has proven that the key principle, the integration of a first amplification stage in a detector-grade sensor material, can provide a comfortable signal to noise ratio of over 40 for a sensor thickness of 50-75 μm. ASICs have been designed and produced to operate a DEPFET pixel detector with the required read-out speed. A complete detector concept is being developed, including solutions for mechanical support, cooling, and services. In this paper, the status of the DEPFET R & D project is reviewed in the light of the requirements of the vertex detector at a future linear e(+)e(-) collider.
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Egea, F. J. et al, Gadea, A., Barrientos, D., & Huyuk, T. (2013). Design and Test of a High-Speed Flash ADC Mezzanine Card for High-Resolution and Timing Performance in Nuclear Structure Experiments. IEEE Trans. Nucl. Sci., 60(5), 3526–3531.
Abstract: This work describes new electronics for the EX-OGAM2 (HP-Ge detector array) and NEDA (BC501A-based neutron detector array). A new digitizing card with high resolution has been designed for gamma-ray and neutron spectroscopy experiments. The higher bandwidth requirement of the NEDA signals, together with the necessity for accuracy, require a high sampling rate in order to preserve the shape for real-time Pulse Shape Analysis (PSA). The PSA is of paramount importance for the NEDA to discriminate between neutrons and gamma-ray signals. Both high resolution and high speed parameters are often difficult to achieve in a single electronic unit. These constraints, together with the need to build new digitizing electronics to improve performance and flexibility of signal analysis in nuclear physics experiments, led to the development a new FADC mezzanine card. In this work, the design and development are described, including the characterization procedure and the preliminary measurement results.
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Egea Canet, F. J. et al, Gadea, A., & Huyuk, T. (2015). Digital Front-End Electronics for the Neutron Detector NEDA. IEEE Trans. Nucl. Sci., 62(3), 1063–1069.
Abstract: This paper presents the design of the NEDA (Neutron Detector Array) electronics, a first attempt to involve the use of digital electronics in large neutron detector arrays. Starting from the front-end modules attached to the PMTs (PhotoMultiplier Tubes) and ending up with the data processing workstations, a comprehensive electronic system capable of dealing with the acquisition and pre-processing of the neutron array is detailed. Among the electronic modules required, we emphasize the front-end analog processing, the digitalization, digital pre-processing and communications firmware, as well as the integration of the GTS (Global Trigger and Synchronization) system, already used successfully in AGATA (Advanced Gamma Tracking Array). The NEDA array will be available for measurements in 2016.
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Bouhova-Thacker, E., Kostyukhin, V., Koffas, T., Liebig, W., Limper, M., Piacquadio, G. N., et al. (2010). Expected Performance of Vertex Reconstruction in the ATLAS Experiment at the LHC. IEEE Trans. Nucl. Sci., 57(2), 760–767.
Abstract: In the harsh environment of the Large Hadron Collider at CERN (design luminosity of 10(34) cm(-2) s(-1)) efficient reconstruction of vertices is crucial for many physics analyses. Described in this paper is the expected performance of the vertex reconstruction used in the ATLAS experiment. The algorithms for the reconstruction of primary and secondary vertices as well as for finding photon conversions and vertex reconstruction in jets are described. The implementation of vertex algorithms which follows a very modular design based on object-oriented C++ is presented. A user-friendly concept allows event reconstruction and physics analyses to compare and optimize their choice among different vertex reconstruction strategies. The performance of implemented algorithms has been studied on a variety of Monte Carlo samples and results are presented.
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