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Author |
Domingo-Pardo, C. |
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Title  |
A new technique for 3D gamma-ray imaging: Conceptual study of a 3D camera |
Type |
Journal Article |
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Year |
2012 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
675 |
Issue |
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Pages |
123-132 |
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Keywords |
Gamma-ray detector; Three dimensional gamma-ray imaging; Compton camera; Gamma camera |
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Abstract |
A novel technique for 3D gamma-ray imaging is presented. This method combines the positron annihilation Compton scattering imaging technique with a supplementary position sensitive detector, which registers gamma-rays scattered in the object at angles of about 90 degrees. The 3D coordinates of the scattering location can be determined rather accurately by applying the Compton principle. This method requires access to the object from two orthogonal sides and allows one to achieve a position resolution of few mm in all three space coordinates. A feasibility study for a 3D camera is presented based on Monte Carlo calculations. |
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Address |
Univ Valencia, Inst Fis Corpuscular, CSIC, E-46071 Valencia, Spain, Email: domingo@ific.uv.es |
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Elsevier Science Bv |
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English |
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ISSN |
0168-9002 |
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Conference |
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Notes |
WOS:000302973600019 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
989 |
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Author |
Muñoz, E.; Barrientos, L.; Bernabeu, J.; Borja-Lloret, M.; Llosa, G.; Ros, A.; Roser, J.; Oliver, J.F. |
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Title |
A spectral reconstruction algorithm for two-plane Compton cameras |
Type |
Journal Article |
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Year |
2020 |
Publication |
Physics in Medicine and Biology |
Abbreviated Journal |
Phys. Med. Biol. |
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Volume |
65 |
Issue |
2 |
Pages |
025011 - 17pp |
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Keywords |
Compton imaging; Compton camera; hadron therapy; image reconstruction |
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Abstract |
One factor limiting the current applicability extent of hadron therapy is the lack of a reliable method for real time treatment monitoring. The use of Compton imaging systems as monitors requires the correct reconstruction of the distribution of prompt gamma productions during patient irradiation. In order to extract the maximum information from all the measurable events, we implemented a spectral reconstruction method that assigns to all events a probability of being either partial or total energy depositions. The method, implemented in a list-mode maximum likelihood expectation maximization algorithm, generates a four dimensional image in the joint spatial-spectral domain, in which the voxels containing the emission positions and energies are obtained. The analytical model used for the system response function is also employed to derive an analytical expression for the sensitivity, which is calculated via Monte Carlo integration. The performance of the method is evaluated through reconstruction of various experimental and simulated sources with different spatial and energy distributions. The results show that the proposed method can recover the spectral and spatial information simultaneously, but only under the assumption of ideal measurements. The analysis of the Monte Carlo simulations has led to the identification of two important degradation sources: the mispositioning of the gamma interaction point and the missing energy recorded in the interaction. Both factors are related to the high energy transferred to the recoil electrons, which can travel far from the interaction point and even escape the detector. These effects prevent the direct application of the current method in more realistic scenarios. Nevertheless, experimental point-like sources have been accurately reconstructed and the spatial distributions and spectral emission of complex simulated phantoms can be identified. |
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Address |
[Munoz, Enrique; Barrientos, Luis; Bernabeu, Jose; Borja-Lloret, Marina; Llosa, Gabriela; Ros, Ana; Roser, Jorge; Oliver, Josep F.] Univ Valencia, CSIC, Inst Fis Corpuscular, Valencia, Spain, Email: Enrique.Munoz@ific.uv.es |
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Iop Publishing Ltd |
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English |
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0031-9155 |
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Notes |
WOS:000520111400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4332 |
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Author |
NEXT Collaboration (Simon, A. et al); Gomez-Cadenas, J. J.; Alvarez, V.; Benlloch-Rodriguez, J. M.; Botas, A.; Carcel, S.; Carrion, J.V.; Diaz, J.; Felkai, R.; Ferrario, P.; Laing, A.; Liubarsky, I.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Muñoz Vidal, J.; Musti, M.; Nebot-Guinot, M.; Novella, P.; Palmeiro, B.; Perez, J.; Querol, M.; Renner, J.; Rodriguez, J.; Sorel, M.; Torrent, J.; Yahlali, N. |
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Title |
Application and performance of an ML-EM algorithm in NEXT |
Type |
Journal Article |
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Year |
2017 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
12 |
Issue |
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Pages |
P08009 - 22pp |
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Keywords |
Gaseous imaging and tracking detectors; Image reconstruction in medical imaging; Time projection Chambers (TPC); Medical-image reconstruction methods and algorithms; computer-aided software |
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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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Address |
[Simon, A.; Gomez-Cadenas, J. J.; Alvarez, V.; Benlloch-Rodriguez, J. M.; Botas, A.; Carcel, S.; Carrion, J. V.; Diaz, J.; Felkai, R.; Ferrario, P.; Laing, A.; Liubarsky, I.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Munoz Vidal, J.; Musti, M.; Nebot-Guinot, M.; Novella, P.; Palmeiro, B.; Perez, J.; Querol, M.; Renner, J.; Rodriguez, J.; Sorel, M.; Torrent, J.; Yahlali, N.] CSIC, Inst Fis Corpuscular IFIC, Calle Catedrat Jose Beltran 2, Valencia 46980, Spain, Email: ander.simon@ific.uv.es |
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Iop Publishing Ltd |
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English |
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ISSN |
1748-0221 |
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Conference |
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Notes |
WOS:000414159500009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3358 |
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Author |
Stoppa, F.; Bhattacharyya, S.; Ruiz de Austri, R.; Vreeswijk, P.; Caron, S.; Zaharijas, G.; Bloemen, S.; Principe, G.; Malyshev, D.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information |
Type |
Journal Article |
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Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
680 |
Issue |
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Pages |
A109 - 16pp |
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Keywords |
methods: data analysis; techniques: image processing; astronomical databases: miscellaneous; stars: imaging; Galaxies: statistics |
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Abstract |
Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy. |
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Address |
[Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl |
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Publisher |
Edp Sciences S A |
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English |
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ISSN |
0004-6361 |
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Conference |
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Notes |
WOS:001131898100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5888 |
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| Permanent link to this record |
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Author |
Stoppa, F.; Ruiz de Austri, R.; Vreeswijk, P.; Bhattacharyya, S.; Caron, S.; Bloemen, S.; Zaharijas, G.; Principe, G.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation |
Type |
Journal Article |
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Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
680 |
Issue |
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Pages |
A108 - 14pp |
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Keywords |
astronomical databases: miscellaneous; methods: data analysis; stars: imaging; techniques: image processing |
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Abstract |
Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities. |
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Address |
[Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys, IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl |
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Edp Sciences S A |
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English |
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0004-6361 |
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Conference |
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Notes |
WOS:001131898100003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5887 |
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Author |
Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Bhattacharyya, S.; Caron, S.; Johannesson, G.; Ruiz de Austri, R.; van den Oetelaar, C.; Zaharijas, G.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian |
Type |
Journal Article |
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Year |
2022 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
662 |
Issue |
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Pages |
A109 - 8pp |
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Keywords |
astronomical databases; miscellaneous; methods; data analysis; stars; imaging; techniques; image processing |
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Abstract |
Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available. |
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Address |
[Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys, IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl |
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Edp Sciences S A |
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English |
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0004-6361 |
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Conference |
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Notes |
WOS:000818665600009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5291 |
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Author |
AGATA Collaboration; Doncel, M.; Quintana, B.; Gadea, A.; Recchia, F.; Farnea, E. |
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Title |
Background rejection capabilities of a Compton imaging telescope setup with a DSSD Ge planar detector and AGATA |
Type |
Journal Article |
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Year |
2011 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
648 |
Issue |
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Pages |
S131-S134 |
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Keywords |
gamma-Spectroscopy; Gamma tracking; Imaging; Position-sensitive germanium detectors |
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Abstract |
In this work, we show the first Monte Carlo results about the performance of the Ge array which we propose for the DESPEC experiment at FAIR, when the background algorithm developed for AGATA is applied. The main objective of our study is to characterize the capabilities of the gamma-spectroscopy system, made up of AGATA detectors in a semi-spherical distribution covering a 1 pi solid angle and a set of planar Ge detectors in a daisy configuration, to discriminate between gamma sources placed at different locations. |
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Address |
[Doncel, M.; Quintana, B.] Univ Salamanca, Lab Radiac Ionizantes, E-37008 Salamanca, Spain, Email: doncel@usal.es |
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Elsevier Science Bv |
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English |
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0168-9002 |
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Notes |
WOS:000305376900035 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
1071 |
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Author |
NEXT Collaboration (Martinez-Lema, G. et al); Palmeiro, B.; Botas, A.; Laing, A.; Renner, J.; Simon, A.; Alvarez, V.; Benlloch-Rodriguez, J.M.; Carcel, S.; Carrion, J.V.; Diaz, J.; Felkai, R.; Kekic, M.; Lopez-March, N.; Martinez, A.; Muñoz Vidal, J.; Musti, M.; Nebot-Guinot, M.; Novella, P.; Perez, J.; Querol, M.; Rodriguez, J.; Romo-Lugue, C.; Sorel, M.; Torrent, J.; Yahlali, N. |
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Title |
Calibration of the NEXT-White detector using Kr-83m decays |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
13 |
Issue |
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Pages |
P10014 - 21pp |
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Keywords |
Charge transport; multiplication and electroluminescence in rare gases and liquids; Gaseous imaging and tracking detectors; Time projection Chambers (TPC); Double-beta decay detectors |
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Abstract |
The NEXT-White (NEW) detector is currently the largest radio-pure high-pressure xenon gas time projection chamber with electroluminescent readout in the world. It has been operating at Laboratorio Subterraneo de Canfranc (LSC) since October 2016. This paper describes the calibrations performed using Kr-83m decays during a long run taken from March to November 2017 (Run II). Krypton calibrations are used to correct for the finite drift-electron lifetime as well as for the dependence of the measured energy on the event transverse position which is caused by variations in solid angle coverage both for direct and reflected light and edge effects. After producing calibration maps to correct for both effects we measure an excellent energy resolution for 41.5 keV point-like deposits of (4.553 +/- 0.010 (stat.) +/- 0.324 (sys.)) % FWHM in the full chamber and (3.804 +/- 0.013 (stat.) +/- 0.112 (sys.)) % FWHM in a restricted fiducial volume. Using naive 1/root E scaling, these values translate into resolutions of (0.5916 +/- 0.0014 (stat.) +/- 0.0421 (sys.)) % FWHM and (0.4943 +/- 0.0017 (stat.) +/- 0.0146 (sys.)) % FWHM at the Q(beta beta) energy of xenon double beta decay (2458 keV), well within range of our target value of 1%. |
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Address |
[Hauptman, J.] Iowa State Univ, Dept Phys & Astron, 12 Phys Hall, Ames, IA 50011 USA, Email: gonzalo.martinez.lema@usc.es |
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Iop Publishing Ltd |
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English |
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1748-0221 |
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Notes |
WOS:000447061800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3754 |
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Author |
Etxebeste, A.; Dauvergne, D.; Fontana, M.; Letang, J.M.; Llosa, G.; Muñoz, E.; Oliver, J.F.; Testa, E.; Sarrut, D. |
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Title |
CCMod: a GATE module for Compton camera imaging simulation |
Type |
Journal Article |
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Year |
2020 |
Publication |
Physics in Medicine and Biology |
Abbreviated Journal |
Phys. Med. Biol. |
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Volume |
65 |
Issue |
5 |
Pages |
055004 - 17pp |
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Keywords |
Monte Carlo; simulation; gamma imaging; Compton camera |
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Abstract |
Compton cameras are gamma-ray imaging systems which have been proposed for a wide variety of applications such as medical imaging, nuclear decommissioning or homeland security. In the design and optimization of such a system Monte Carlo simulations play an essential role. In this work, we propose a generic module to perform Monte Carlo simulations and analyses of Compton Camera imaging which is included in the open-source GATE/Geant4 platform. Several digitization stages have been implemented within the module to mimic the performance of the most commonly employed detectors (e.g. monolithic blocks, pixelated scintillator crystals, strip detectors...). Time coincidence sorter and sequence coincidence reconstruction are also available in order to aim at providing modules to facilitate the comparison and reproduction of the data taken with different prototypes. All processing steps may be performed during the simulation (on-the-fly mode) or as a post-process of the output files (offline mode). The predictions of the module have been compared with experimental data in terms of energy spectra, angular resolution, efficiency and back-projection image reconstruction. Consistent results within a 3-sigma interval were obtained for the energy spectra except for low energies where small differences arise. The angular resolution measure for incident photons of 1275 keV was also in good agreement between both data sets with a value close to 13 degrees. Moreover, with the aim of demonstrating the versatility of such a tool the performance of two different Compton camera designs was evaluated and compared. |
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Address |
[Etxebeste, A.; Letang, J. M.; Sarrut, D.] Univ Lyon 1, Univ Lyon, CREATIS, CNRS UMR5220,Inserm U1044,INSA Lyon, Lyon, France, Email: ane.etxebeste@creatis.insa-lyon.fr |
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Iop Publishing Ltd |
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English |
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ISSN |
0031-9155 |
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Notes |
WOS:000519034800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4321 |
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Author |
Albiol, F.; Corbi, A.; Albiol, A. |
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Title |
Densitometric Radiographic Imaging With Contour Sensors |
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Journal Article |
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Year |
2019 |
Publication |
IEEE Access |
Abbreviated Journal |
IEEE Access |
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Volume |
7 |
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Pages |
18902-18914 |
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Keywords |
Conventional X-ray imaging; contour data; densitometric images; dynamic range; depth information |
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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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Address |
[Albiol, Francisco; Corbi, Alberto] CSIC, Inst Fis Corpuscular, Paterna 46980, Spain, Email: kiko@ific.uv.es |
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Publisher |
Ieee-Inst Electrical Electronics Engineers Inc |
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Language |
English |
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ISSN |
2169-3536 |
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Notes |
WOS:000459591800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3920 |
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