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Linhart, V., Burdette, D., Chessi, E., Cindro, V., Clinthorne, N. H., Cochran, E., et al. (2011). Spectroscopy study of imaging devices based on silicon Pixel Array Detector coupled to VATAGP7 read-out chips. J. Instrum., 6, C01092–8pp.
Abstract: Spectroscopic and timing response studies have been conducted on a detector module consisting of a silicon Pixel Array Detector bonded on two VATAGP7 read-out chips manufactured by Gamma-Medica Ideas using laboratory gamma sources and the internal calibration facilities (the calibration system of the read-out chips). The performed tests have proven that the chips have (i) non-linear calibration curves which can be approximated by power functions, (ii) capability to measure the energy of photons with energy resolution better than 2 keV (exact range and resolution depend on experimental setup), (iii) the internal calibration facility which provides 6 out of 16 available internal calibration charges within our region of interest (spanning the Compton edge of 511 keV photons). The peaks induced by the internal calibration facility are suitable for a fit of the calibration curves. However, they are not suitable for measurements of equivalent noise charge because their full width at half maximum varies with their amplitude. These facts indicate that the VATAGP7 chips are useful and precise tools for a wide variety of spectroscopic devices. We have also explored time walk of the module and peaking time of the spectroscopy signals provided by the chips. We have observed that (iv) the time walk is caused partly by the peaking time of the signals provided by the fast shaper of the chips and partly by the timing uncertainty related to the varying position of the photon interaction, (v) the peaking time of the spectroscopy signals provided by the chips increases with increasing pulse height.
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Albiol, F., Corbi, A., & Albiol, A. (2019). Densitometric Radiographic Imaging With Contour Sensors. IEEE Access, 7, 18902–18914.
Abstract: We present the technical/physical foundations of a new imaging technique that combines ordinary radiographic information (generated by conventional X-ray settings) with the patient's volume to derive densitometric images. Traditionally, these images provide quantitative information about tissues densities. In our approach, they graphically enhance either soft or bony regions. After measuring the patient's volume with contour recognition devices, the physical traversed lengths within it (as the Roentgen beam intersects the patient) are calculated and pixel-wise associated with the original radiograph (X). In order to derive this map of lengths (L), the camera equations of the X-ray system and the contour sensor are determined. The patient's surface is also translated to the point-of-view of the X-ray beam and all its entrance/exit points are sought with the help of ray-casting methods. The derived L is applied to X as a physical operation (subtraction), obtaining soft tissue-(D-S) or bone-enhanced (D'(B)) figures. In the D-S type, the contained graphical information can be linearly mapped to the average electronic density (traversed by the X-ray beam). This feature represents an interesting proof-of-concept of associating density data to radiographs, but most important, their intensity histogram is objectively compressed, i.e., the dynamic range is more shrunk (compared against the corresponding X). This leads to other advantages: improvement in the visibility of border/edge areas (high gradient), extended manual window level/width manipulations during screening, and immediate correction of underexposed X instances. In the D-B' type, high-density elements are highlighted and easier to discern. All these results can be achieved with low-energy beam exposures, saving costs and dose. Future work will deepen this clinical side of our research. In contrast with other image-based modifiers, the proposed method is grounded on the measurement of a physical entity: the span of the X-ray beam within a body while undertaking a radiographic examination.
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NEXT Collaboration(Alvarez, V. et al), Ball, M., Carcel, S., Cervera-Villanueva, A., Diaz, J., Ferrario, P., et al. (2013). Design and characterization of the SiPM tracking system of NEXT-DEMO, a demonstrator prototype of the NEXT-100 experiment. J. Instrum., 8, T05002–18pp.
Abstract: NEXT-100 experiment aims at searching the neutrinoless double-beta decay of the Xe-136 isotope using a TPC filled with a 100 kg of high-pressure gaseous xenon, with 90% isotopic enrichment. The experiment will take place at the Laboratorio Subterraneo de Canfranc (LSC), Spain. NEXT-100 uses electroluminescence (EL) technology for energy measurement with a resolution better than 1% FWHM. The gaseous xenon in the TPC additionally allows the tracks of the two beta particles to be recorded, which are expected to have a length of up to 30 cm at 10 bar pressure. The ability to record the topological signature of the beta beta 0 nu events provides a powerful background rejection factor for the beta beta experiment. In this paper, we present a novel 3D imaging concept using SiPMs coated with tetraphenyl butadiene (TPB) for the EL read out and its first implementation in NEXT-DEMO, a large-scale prototype of the NEXT-100 experiment. The design and the first characterization measurements of the NEXT-DEMO SiPM tracking system are presented. The SiPM response uniformity over the tracking plane drawn from its gain map is shown to be better than 4%. An automated active control system for the stabilization of the SiPMs gain was developed, based on the voltage supply compensation of the gain drifts. The gain is shown to be stabilized within 0.2% relative variation around its nominal value, provided by Hamamatsu, in a temperature range of 10 degrees C. The noise level from the electronics and the SiPM dark noise is shown to lay typically below the level of 10 photoelectrons (pe) in the ADC. Hence, a detection threshold at 10 pe is set for the acquisition of the tracking signals. The ADC full dynamic range (4096 channels) is shown to be adequate for signal levels of up to 200 pe/mu s, which enables recording most of the tracking signals.
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Lerendegui-Marco, J., Babiano-Suarez, V., Balibrea-Correa, J., Caballero, L., Calvo, D., Ladarescu, I., et al. (2024). Simultaneous Gamma-Neutron Vision device: a portable and versatile tool for nuclear inspections. EPJ Tech. Instrum., 11(1), 2–17pp.
Abstract: This work presents GN-Vision, a novel dual gamma-ray and neutron imaging system, which aims at simultaneously obtaining information about the spatial origin of gamma-ray and neutron sources. The proposed device is based on two position sensitive detection planes and exploits the Compton imaging technique for the imaging of gamma-rays. In addition, spatial distributions of slow- and thermal-neutron sources (<100 eV) are reconstructed by using a passive neutron pin-hole collimator attached to the first detection plane. The proposed gamma-neutron imaging device could be of prime interest for nuclear safety and security applications. The two main advantages of this imaging system are its high efficiency and portability, making it well suited for nuclear applications were compactness and real-time imaging is important. This work presents the working principle and conceptual design of the GN-Vision system and explores, on the basis of Monte Carlo simulations, its simultaneous gamma-ray and neutron detection and imaging capabilities for a realistic scenario where a Cf-252 source is hidden in a neutron moderating container.
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NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
Abstract: The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.
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