Brzezinski, K., Oliver, J. F., Gillam, J., & Rafecas, M. (2014). Study of a high-resolution PET system using a Silicon detector probe. Phys. Med. Biol., 59(20), 6117–6140.
Abstract: A high-resolution silicon detector probe, in coincidence with a conventional PET scanner, is expected to provide images of higher quality than those achievable using the scanner alone. Spatial resolution should improve due to the finer pixelization of the probe detector, while increased sensitivity in the probe vicinity is expected to decrease noise. A PET-probe prototype is being developed utilizing this principle. The system includes a probe consisting of ten layers of silicon detectors, each a 80 x 52 array of 1 x 1 x 1 mm(3) pixels, to be operated in coincidence with a modern clinical PET scanner. Detailed simulation studies of this system have been performed to assess the effect of the additional probe information on the quality of the reconstructed images. A grid of point sources was simulated to study the contribution of the probe to the system resolution at different locations over the field of view (FOV). A resolution phantom was used to demonstrate the effect on image resolution for two probe positions. A homogeneous source distribution with hot and cold regions was used to demonstrate that the localized improvement in resolution does not come at the expense of the overall quality of the image. Since the improvement is constrained to an area close to the probe, breast imaging is proposed as a potential application for the novel geometry. In this sense, a simplified breast phantom, adjacent to heart and torso compartments, was simulated and the effect of the probe on lesion detectability, through measurements of the local contrast recovery coefficient-to-noise ratio (CNR), was observed. The list-mode ML-EM algorithm was used for image reconstruction in all cases. As expected, the point spread function of the PET-probe system was found to be non-isotropic and vary with position, offering improvement in specific regions. Increase in resolution, of factors of up to 2, was observed in the region close to the probe. Images of the resolution phantom showed visible improvement in resolution when including the probe in the simulations. The image quality study demonstrated that contrast and spill-over ratio in other areas of the FOV were not sacrificed for this enhancement. The CNR study performed on the breast phantom indicates increased lesion detectability provided by the probe.
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LHCb Collaboration(Aaij, R. et al), Martinez-Vidal, F., Oyanguren, A., Ruiz Valls, P., & Sanchez Mayordomo, C. (2014). Precision luminosity measurements at LHCb. J. Instrum., 9, P12005–91pp.
Abstract: Measuring cross-sections at the LHC requires the luminosity to be determined accurately at each centre-of-mass energy root s. In this paper results are reported from the luminosity calibrations carried out at the LHC interaction point 8 with the LHCb detector for root s = 2.76, 7 and 8TeV (proton-proton collisions) and for root s(NN) = 5TeV (proton-lead collisions). Both the “van der Meer scan” and “beam-gas imaging” luminosity calibration methods were employed. It is observed that the beam density profile cannot always be described by a function that is factorizable in the two transverse coordinates. The introduction of a two-dimensional description of the beams improves significantly the consistency of the results. For proton-proton interactions at root s = 8TeV a relative precision of the luminosity calibration of 1.47% is obtained using van der Meer scans and 1.43% using beam-gas imaging, resulting in a combined precision of 1.12%. Applying the calibration to the full data set determines the luminosity with a precision of 1.16%. This represents the most precise luminosity measurement achieved so far at a bunched-beam hadron collider.
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Esperante-Pereira, D. (2014). DEPFET active pixel sensors for the vertex detector of the Belle-II experiment. J. Instrum., 9, C03004–11pp.
Abstract: Active pixels sensors based on the DEPFET technology will be used for the innermost vertex detector of the future Belle-II experiment. The increased luminosity of the e(+) e(-) SuperKEKB collider entails challenging detector requirements, namely: low material budget, low power consumption, high precision and efficiency, and a large readout rate. The DEPFET active pixel technology has shown to be a suitable solution for this purpose. A review of the different aspects of the detector design (sensors, readout ASICS and supplementary infrastructure) and the results of the latest thinned sensor prototypes (50 μm) are described.
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Gonzalez-Sevilla, S. et al, Bernabeu Verdu, J., Civera, J. V., Garcia, C., Lacasta, C., Marco, R., et al. (2014). A double-sided silicon micro-strip Super-Module for the ATLAS Inner Detector upgrade in the High-Luminosity LHC. J. Instrum., 9, P02003–37pp.
Abstract: The ATLAS experiment is a general purpose detector aiming to fully exploit the discovery potential of the Large Hadron Collider (LHC) at CERN. It is foreseen that after several years of successful data-taking, the LHC physics programme will be extended in the so-called High-Luminosity LHC, where the instantaneous luminosity will be increased up to 5 x 10(34) cm(-2) s(-1). For ATLAS, an upgrade scenario will imply the complete replacement of its internal tracker, as the existing detector will not provide the required performance due to the cumulated radiation damage and the increase in the detector occupancy. The current baseline layout for the new ATLAS tracker is an all-silicon-based detector, with pixel sensors in the inner layers and silicon micro-strip detectors at intermediate and outer radii. The super-module is an integration concept proposed for the strip region of the future ATLAS tracker, where double-sided stereo silicon micro-strip modules are assembled into a low-mass local support structure. An electrical super-module prototype for eight double-sided strip modules has been constructed. The aim is to exercise the multi-module readout chain and to investigate the noise performance of such a system. In this paper, the main components of the current super-module prototype are described and its electrical performance is presented in detail.
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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Ferrer, A., Fiorini, L., et al. (2014). A neural network clustering algorithm for the ATLAS silicon pixel detector. J. Instrum., 9, P09009–34pp.
Abstract: A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.
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