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Author |
Babiano, V.; Caballero, L.; Calvo, D.; Ladarescu, I.; Olleros, P.; Domingo-Pardo, C. |
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Title |
gamma-Ray position reconstruction in large monolithic LaCl3(Ce) crystals with SiPM readout |
Type |
Journal Article |
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Year |
2019 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
931 |
Issue |
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Pages |
1-22 |
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Keywords |
Gamma-ray; Position-sensitive detectors; Monolithic crystals; Spatial resolution; Neural networks |
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Abstract |
We report on the spatial response characterization of large LaCl3(Ce) monolithic crystals optically coupled to 8 x 8 pixel silicon photomultiplier (SiPM) sensors. A systematic study has been carried out for 511 keV gamma-rays using three different crystal thicknesses of 10 mm, 20 mm and 30 mm, all of them with planar geometry and a base size of 50 x 50 mm(2). In this work we investigate and compare two different approaches for the determination of the main gamma-ray hit location. On one hand, methods based on the fit of an analytical model for the scintillation light distribution provide the best results in terms of linearity and field of view, with spatial resolutions close to similar to 1 mm FWHM. On the other hand, position reconstruction techniques based on neural networks provide similar linearity and field-of-view, becoming the attainable spatial resolution similar to 3 mm FWHM. For the third space coordinate z or depth-of-interaction we have implemented an inverse linear calibration approach based on the cross-section of the measured scintillation-light distribution at a certain height. The detectors characterized in this work are intended for the development of so-called Total Energy Detectors with Compton imaging capability (i-TED), aimed at enhanced sensitivity and selectivity measurements of neutron capture cross sections via the time-of-flight (TOF) technique. |
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Address |
[Babiano, V; Caballero, L.; Calvo, D.; Ladarescu, I; Olleros, P.; Domingo-Pardo, C.] Univ Valencia, Inst Fis Corpuscular, CSIC, Valencia, Spain, Email: domingo@ific.uv.es |
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Publisher |
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:000466151600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number  |
IFIC @ pastor @ |
Serial |
4015 |
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Author |
Babiano, V.; Balibrea, J.; Caballero, L.; Calvo, D.; Ladarescu, I.; Mira Prats, S.; Domingo-Pardo, C. |
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Title |
First i-TED demonstrator: A Compton imager with Dynamic Electronic Collimation |
Type |
Journal Article |
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Year |
2020 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
953 |
Issue |
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Pages |
163228 - 9pp |
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Keywords |
Compton imaging; Position-sensitive detectors; Monolithic crystals; Silicon photomultiplier |
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Abstract |
i-TED consists of both a total energy detector and a Compton camera primarily intended for the measurement of neutron capture cross sections by means of the simultaneous combination of neutron time-of-flight (TOF) and gamma-ray imaging techniques. TOF allows one to obtain a neutron-energy differential capture yield, whereas the imaging capability is intended for the discrimination of radiative background sources, that have a spatial origin different from that of the capture sample under investigation. A distinctive feature of i-TED is the embedded Dynamic Electronic Collimation (DEC) concept, which allows for a trade-off between efficiency and image resolution. Here we report on some general design considerations and first performance characterization measurements made with an i-TED demonstrator in order to explore its gamma-ray detection and imaging capabilities. |
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Address |
[Babiano, V; Balibrea, J.; Caballero, L.; Calvo, D.; Ladarescu, I; Mira Prats, S.; Domingo-Pardo, C.] Univ Valencia, CSIC, Inst Fis Corpuscular, Valencia, Spain, Email: domingo@ific.uv.es |
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Elsevier |
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English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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ISSN |
0168-9002 |
ISBN |
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Conference |
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Notes |
WOS:000506419900045 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4250 |
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Author |
n_TOF Collaboration (Mazzone, A. et al); Babiano-Suarez, V; Caballero, L.; Domingo-Pardo, C.; Ladarescu, I; Tain, J.L. |
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Title |
Measurement of the Gd-154(n, gamma) cross section and its astrophysical implications |
Type |
Journal Article |
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Year |
2020 |
Publication |
Physics Letters B |
Abbreviated Journal |
Phys. Lett. B |
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Volume |
804 |
Issue |
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Pages |
135405 - 6pp |
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Keywords |
s process; Gd-154; Neutron time of flight; n_TOF |
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Abstract |
The neutron capture cross section of Gd-154 was measured from 1 eV to 300 keV in the experimental area located 185 m from the CERN n_TOF neutron spallation source, using a metallic sample of gadolinium, enriched to 67% in Gd-154. The capture measurement, performed with four C6D6 scintillation detectors, has been complemented by a transmission measurement performed at the GELINA time-of-flight facility (JRC-Geel), thus minimising the uncertainty related to sample composition. An accurate Maxwellian averaged capture cross section (MACS) was deduced over the temperature range of interest for s process nucleosynthesis modelling. We report a value of 880(50) mb for the MACS at kT = 30 keV, significantly lower compared to values available in literature. The new adopted Gd-154(n, gamma) cross section reduces the discrepancy between observed and calculated solar s-only isotopic abundances predicted by s-process nucleosynthesis models. |
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Address |
[Mazzone, A.; Barbagallo, M.; Colonna, N.; Damone, L. A.; Tagliente, G.; Variale, V.] Ist Nazl Fis Nucl, Bari, Italy, Email: Cristian.Massimi@bo.infn.it |
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Publisher |
Elsevier |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0370-2693 |
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Conference |
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Notes |
WOS:000548740300022 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4464 |
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Author |
Balibrea-Correa, J.; Lerendegui-Marco, J.; Calvo, D.; Caballero, L.; Babiano, V.; Ladarescu, I.; Redondo, M.L.; Tain, J.L.; Tolosa, A.; Domingo-Pardo, C.; Calvino, F.; Casanovas, A.; Tarifeño-Saldivia, A.; Alcayne, V.; Cano-Ott, D.; Martinez, T.; Guerrero, C.; Barbagallo, M.; Macina, D.; Bacak, M. |
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Title |
A first prototype of C6D6 total-energy detector with SiPM readout for neutron capture time-of-flight experiments |
Type |
Journal Article |
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Year |
2021 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
985 |
Issue |
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Pages |
164709 - 8pp |
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Keywords |
Silicon photomultiplier; Radiation detectors; Time-of-flight; Radiative capture; Total energy detector; Pulse-height weighting technique |
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Abstract |
Low efficiency total-energy detectors (TEDs) are one of the main tools for neutron capture cross section measurements utilizing the time-of-flight (TOF) technique. State-of-the-art TEDs are based on a C6D6 liquid-scintillation cell optically coupled to a fast photomultiplier tube. The large photomultiplier tube represents yet a significant contribution to the so-called neutron sensitivity background, which is one of the most conspicuous sources of uncertainty in this type of experiments. Here we report on the development of a first prototype of a TED based on a silicon-photomultiplier (SiPM) readout, thus resulting in a lightweight and much more compact detector. Apart from the envisaged improvement in neutron sensitivity, the new system uses low voltage (+28 V) and low current supply (-50 mA), which is more practical than the-kV supply required by conventional photomultipliers. One important difficulty hindering the earlier implementation of SiPM readout for this type of detector was the large capacitance for the output signal when all pixels of a SiPM array are summed together. The latter leads to long pulse rise and decay times, which are not suitable for time-of-flight experiments. In this work we demonstrate the feasibility of a Schottky-diode multiplexing readout approach, that allows one to preserve the excellent timing properties of SiPMs, hereby paving the way for their implementation in future neutron TOF experiments. |
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Address |
[Balibrea-Correa, J.; Lerendegui-Marco, J.; Calvo, D.; Caballero, L.; Babiano, V; Ladarescu, I; Redondo, M. Lopez; Tain, J. L.; Tolosa, A.; Domingo-Pardo, C.] Univ Valencia, Inst Fis Corpuscular, CSIC, Valencia, Spain, Email: dacaldia@ific.uv.es; |
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Publisher |
Elsevier |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0168-9002 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000592358200019 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4638 |
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Author |
Schaffter, T. et al; Albiol, F.; Caballero, L. |
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Title |
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms |
Type |
Journal Article |
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Year |
2020 |
Publication |
JAMA Network Open |
Abbreviated Journal |
JAMA Netw. Open |
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Volume |
3 |
Issue |
3 |
Pages |
e200265 - 15pp |
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Keywords |
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Abstract |
Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results Overall, 144231 screening mammograms from 85580 US women (952 cancer positive <= 12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166578 examinations from 68008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation. Question How do deep learning algorithms perform compared with radiologists in screening mammography interpretation? Findings In this diagnostic accuracy study using 144231 screening mammograms from 85580 women from the United States and 166578 screening mammograms from 68008 women from Sweden, no single artificial intelligence algorithm outperformed US community radiologist benchmarks; including clinical data and prior mammograms did not improve artificial intelligence performance. However, combining best-performing artificial intelligence algorithms with single-radiologist assessment demonstrated increased specificity. Meaning Integrating artificial intelligence to mammography interpretation in single-radiologist settings could yield significant performance improvements, with the potential to reduce health care system expenditures and address resource scarcity experienced in population-based screening programs. This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms. |
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Address |
[Schaffter, Thomas; Hoff, Bruce; Yu, Thomas; Neto, Elias Chaibub; Friend, Stephen; Guinney, Justin] Sage Bionetworks, Computat Oncol, Seattle, WA USA, Email: gustavo@us.ibm.com |
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Corporate Author |
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Thesis |
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Publisher |
Amer Medical Assoc |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2574-3805 |
ISBN |
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Conference |
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Notes |
WOS:000519249800002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4683 |
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