Geant4-GATE simulation of a large plastic scintillator for muon radiography

Aguiar, Pablo; Casarejos, E.; Vilán, José Antonio Vilán; Iglesias, A.

doi:10.1109/animma.2013.6728082

Cited by 7 publications

(6 citation statements)

References 11 publications

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“…GATE incorporates the well-validated physics of GEANT4 with a more user-friendly simulation environment [20]. GATE has shown great potential in a wide range of medical applications, including radiotherapy [21][22][23], diagnostic radiology [24,25], and dosimetry [26][27][28].…”

Section: Methodsmentioning

confidence: 99%

Production of actinium-225 from a (n,p) reaction: Feasibility and pre-design studies

et al. 2021

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Actinium-225 is used in nuclear medicine for the treatment of malignant tumours. It can be applied to produce Bi-213 in a reusable generator or can be used alone as an agent for radiation therapy, in particular for targeted alpha therapy. However, the availability of Ac-225 for worldwide use, particularly in low- and middle-income countries, is limited. We present a feasibility study employing GATE, an open-source Monte Carlo simulation toolkit, on the production of Ac-225 from a neutron generator. This work suggests that a design consisting of three concentric cylinders, the innermost a Cf-252 neutron source, the middle nickel cylinder acting as a proton-producing target and the outer cylinder a RaCl2 target may provide a feasible design outline for an Ac-225 generator.

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Section: Methodsmentioning

confidence: 99%

Production of actinium-225 from a (n,p) reaction: Feasibility and pre-design studies

et al. 2021

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“…However, the low performance of such methods motivated researchers to look for alternative techniques. Aguiar et al simulated a plate detector and used Anger logic for localization of the muon hits [ 7 ]. Recently, thanks to the latest technological developments, machine learning-based methods have become popular, in addition to the analytical methods for estimating the particle hit position.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Neural Networks and Center of Gravity in Muon Hit Position Estimation

Aktas

Kiisk

Giammanco

et al. 2022

Entropy

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The performance of cosmic-ray tomography systems is largely determined by their tracking accuracy. With conventional scintillation detector technology, good precision can be achieved with a small pitch between the elements of the detector array. Improving the resolution implies increasing the number of read-out channels, which in turn increases the complexity and cost of the tracking detectors. As an alternative to that, a scintillation plate detector coupled with multiple silicon photomultipliers could be used as a technically simple solution. In this paper, we present a comparison between two deep-learning-based methods and a conventional Center of Gravity (CoG) algorithm, used to calculate cosmic-ray muon hit positions on the plate detector using the signals from the photomultipliers. In this study, we generated a dataset of muon hits on a detector plate using the Monte Carlo simulation toolkit GEANT4. We demonstrate that two deep-learning-based methods outperform the conventional CoG algorithm by a significant margin. Our proposed algorithm, Fully Connected Network, produces a 0.72 mm average error measured in Euclidean distance between the actual and predicted hit coordinates, showing great improvement in comparison with CoG, which yields 1.41 mm on the same dataset. Additionally, we investigated the effects of different sensor configurations on performance.

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“…Muography is a non-invasive technique for imaging anthropic and geologic structures [1][2][3][4][5][6][7][8][9][10][11][12] by measuring the crossing muon flux using sensitive hodoscopes made of nuclear emulsions [2,13], gaseous chambers [14][15][16][17] and scintillators [4,8,11,[18][19][20]. Scintillation hodoscopes provide flexibility on the implementation, low cost, and robustness against environmental variables such as humidity, temperature, and atmospheric pressure [21].…”

Section: Introductionmentioning

confidence: 99%

Characterization and on-field performance of the MuTe Silicon Photomultipliers

Sánchez-Villafrades¹,

Peña-Rodríguez²,

Asorey³

et al. 2021

Preprint

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A: The Muon Telescope is a muography experiment for imaging volcanoes in Colombia. It consists of a scintillator tracking system and a water Cherenkov detector used for particle deposited energy measurement. The MuTe operates autonomously in high altitude environments where the temperature gradient reaches up to 10 • C. In this work, we characterize the breakdown voltage, gain, and noise of the telescope silicon photomultipliers for temperature variations spanning 0 to 40 • C. We demonstrated that the discrimination threshold for the MuTe hodoscope must be above 5 pe to avoid contamination due to the SiPM dark count, crosstalk, and afterpulsing. We also assess the MuTe counting rate depending on day-night temperature variations.

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Geant4-GATE simulation of a large plastic scintillator for muon radiography

Cited by 7 publications

References 11 publications

Production of actinium-225 from a (n,p) reaction: Feasibility and pre-design studies

Production of actinium-225 from a (n,p) reaction: Feasibility and pre-design studies

A Comparison of Neural Networks and Center of Gravity in Muon Hit Position Estimation

Characterization and on-field performance of the MuTe Silicon Photomultipliers

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