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Author Carles, M.; Lerche, C.W.; Sanchez, F.; Mora, F.; Benlloch, J.M.
Title Position correction with depth of interaction information for a small animal PET system Type Journal Article
Year 2011 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A
Volume 648 Issue Pages S176-S180
Keywords DOI; PET; Positioning algorithm; Gamma ray imaging; Continuous scintillators
Abstract In this work we study the effects on the spatial resolution when depth of interaction (001) information is included in the parameterization of the line of response (LOR) for a small animal positron emission tomography (PET) system. One of the most important degrading factors for PET is the parallax error introduced in systems that do not provide DOI information of the recorded gamma-rays. Our group has designed a simple and inexpensive method for DOI determination in continuous scintillation crystals. This method is based, on one hand, in the correlation between the scintillation light distribution width in monolithic crystals and the DOI, and, on the other hand, on a small modification of the widely applied charge dividing circuits (CDR). In this work we present a new system calibration that includes the DOI information, and also the development of the correction equations that relates the LOR without and with DOI information. We report the results obtained for different measurements along the transaxial field of view (FOV) and the image quality enhancement achieved specially at the edge of the FOV.
Address (up) [Carles, M.; Sanchez, F.; Benlloch, J. M.] Inst Fis Corpuscular CSIC UV, Valencia 46071, Spain, Email: montcar@ific.uv.es
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-9002 ISBN Medium
Area Expedition Conference
Notes WOS:000305376900046 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 1067
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Author Caron, S.; Gomez-Vargas, G.A.; Hendriks, L.; Ruiz de Austri, R.
Title Analyzing gamma rays of the Galactic Center with deep learning Type Journal Article
Year 2018 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.
Volume 05 Issue 5 Pages 058 - 24pp
Keywords gamma ray experiments; dark matter simulations
Abstract We present the application of convolutional neural networks to a particular problem in gamma ray astronomy. Explicitly, we use this method to investigate the origin of an excess emission of GeV gamma rays in the direction of the Galactic Center, reported by several groups by analyzing Fermi-LAT data. Interpretations of this excess include gamma rays created by the annihilation of dark matter particles and gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. We train and test convolutional neural networks with simulated Fermi-LAT images based on point and diffuse emission models of the Galactic Center tuned to measured gamma ray data. Our new method allows precise measurements of the contribution and properties of an unresolved population of gamma ray point sources in the interstellar diffuse emission model. The current model predicts the fraction of unresolved point sources with an error of up to 10% and this is expected to decrease with future work.
Address (up) [Caron, Sascha; Hendriks, Luc] Radboud Univ Nijmegen, Fac Sci, Inst Math Astrophys & Particle Phys, Mailbox 79,POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: scaron@cern.ch;
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1475-7516 ISBN Medium
Area Expedition Conference
Notes WOS:000432869300005 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 3582
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Author Caron, S.; Eckner, C.; Hendriks, L.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G.
Title Mind the gap: the discrepancy between simulation and reality drives interpretations of the Galactic Center Excess Type Journal Article
Year 2023 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.
Volume 06 Issue 6 Pages 013 - 56pp
Keywords dark matter simulations; gamma ray experiments; Machine learning; millisecond pulsars
Abstract The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model (-yEM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of-yEMs with increasing parametric freedom. We calculate the fractional contribution (fsrc) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the ryEM. For the simplest ryEM, we obtain fsrc = 0.10 f 0.07, while the most complex model yields fsrc = 0.79 f 0.24. In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed ryEM. The quoted results for fsrc do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated ryEM iterations. We quantify the reality gap between our ryEMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed ryEMs have gaps to reality. Our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked “out of domain” uncertainties in future interpretations.
Address (up) [Caron, Sascha; Hendriks, Luc] Radboud Univ Nijmegen, Theoret High Energy Phys, Heyendaalseweg 135, NL-6525 AJ Nijmegen, Netherlands, Email: scaron@nikhef.nl;
Corporate Author Thesis
Publisher IOP Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1475-7516 ISBN Medium
Area Expedition Conference
Notes WOS:001025516000009 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5576
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Author Carrasco, N.; Ciuchini, M.; Dimopoulos, P.; Frezzotti, R.; Gimenez, V.; Herdoiza, G.; Lubicz, V.; Michael, C.; Picca, E.; Rossi, G.C.; Sanfilippo, F.; Shindler, A.; Silvestrini, L.; Simula, S.; Tarantino, C.
Title B-physics from N-f=2 tmQCD: the Standard Model and beyond Type Journal Article
Year 2014 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 03 Issue 3 Pages 016 - 52pp
Keywords Lattice QCD; B-Physics; Beyond Standard Model; Quark Masses and SM Parameters
Abstract We present a lattice QCD computation of the b-quark mass, the B and B-s decay constants, the B-mixing bag parameters for the full four-fermion operator basis as well as determinations for xi and f(Bq) root B-i((q)) extrapolated to the continuum limit and to the physical pion mass. We used N-f = 2 twisted mass Wilson fermions at four values of the lattice spacing with pion masses ranging from 280 to 500 MeV. Extrapolation in the heavy quark mass from the charm to the bottom quark region has been carried out on ratios of physical quantities computed at nearby quark masses, exploiting the fact that they have an exactly known infinite mass limit. Our results are m(b)(m(b), (MS) over bar) = 4.29(12) GeV, f(Bs) = 228(8) MeV, f(B) = 189(8) MeV and f(Bs)/f(B) = 1.206(24). Moreover with our results for the bag-parameters we find xi = 1.225(31), B-1((s))/B-1((d)) = 1.01(2), f (Bd) root(B) over cap ((d))(1) = 216(10) MeV and integral Bs root(B) over cap ((s))(1) = 262(10) MeV. We also computed the bag parameters for the complete basis of the four-fermion operators which are required in beyond the SM theories. By using these results for the bag parameters we are able to provide a refined Unitarity Triangle analysis in the presence of New Physics, improving the bounds coming from B-(s) -(B) over bar ((s)) mixing.
Address (up) [Carrasco, N.; Gimenez, V.] Univ Valencia, CSIC, Dept Fis Teor, E-46100 Valencia, Spain, Email: nuria.carrasco@uv.es;
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1029-8479 ISBN Medium
Area Expedition Conference
Notes WOS:000347824200001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 2086
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Author Carrasco-Ribelles, L.A.; Pardo-Mas, J.R.; Tortajada, S.; Saez, C.; Valdivieso, B.; Garcia-Gomez, J.M.
Title Predicting morbidity by local similarities in multi-scale patient trajectories Type Journal Article
Year 2021 Publication Journal of Biomedical Informatics Abbreviated Journal J. Biomed. Inform.
Volume 120 Issue Pages 103837 - 9pp
Keywords Patient trajectory; Risk prediction; Local alignment; Dynamic programming; Diabetes; Cardiovascular disease
Abstract Patient Trajectories (PTs) are a method of representing the temporal evolution of patients. They can include information from different sources and be used in socio-medical or clinical domains. PTs have generally been used to generate and study the most common trajectories in, for instance, the development of a disease. On the other hand, healthcare predictive models generally rely on static snapshots of patient information. Only a few works about prediction in healthcare have been found that use PTs, and therefore benefit from their temporal dimension. All of them, however, have used PTs created from single-source information. Therefore, the use of longitudinal multi-scale data to build PTs and use them to obtain predictions about health conditions is yet to be explored. Our hypothesis is that local similarities on small chunks of PTs can identify similar patients concerning their future morbidities. The objectives of this work are (1) to develop a methodology to identify local similarities between PTs before the occurrence of morbidities to predict these on new query individuals; and (2) to validate this methodology on risk prediction of cardiovascular diseases (CVD) occurrence in patients with diabetes. We have proposed a novel formal definition of PTs based on sequences of longitudinal multi-scale data. Moreover, a dynamic programming methodology to identify local alignments on PTs for predicting future morbidities is proposed. Both the proposed methodology for PT definition and the alignment algorithm are generic to be applied on any clinical domain. We validated this solution for predicting CVD in patients with diabetes and we achieved a precision of 0.33, a recall of 0.72 and a specificity of 0.38. Therefore, the proposed solution in the diabetes use case can result of utmost utility to secondary screening.
Address (up) [Carrasco-Ribelles, Lucia A.; Pardo-Mas, Jose Ramon; Saez, Carlos; Garcia-Gomez, Juan M.] Univ Politecn Valencia, Biomed Data Sci Lab BDSLAB, Inst Tecnol Informat & Comunicac ITACA, Camino Vera S-N, Valencia 46022, Spain, Email: lucarri@etsii.upv.es;
Corporate Author Thesis
Publisher Academic Press Inc Elsevier Science Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1532-0464 ISBN Medium
Area Expedition Conference
Notes WOS:000683527500003 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 4934
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