First i-TED demonstrator: A Compton imager with Dynamic Electronic Collimation

Babiano, V.; Balibrea, J.; Caballero, L.; Calvo, D.; Ladarescu, I.; Lerendegui, J.; Prats, Santiago Mira; Domingo‐Pardo, C.

doi:10.1016/j.nima.2019.163228

Cited by 28 publications

(54 citation statements)

References 52 publications

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“…The details on the apparatus and the experiment can be found in [8]. The reconstruction of the γ-ray energy depositions and interaction points in i-TED were based on our previous works [9,10].…”

Section: Compton Imaging For Background Rejection: Proof-of-conceptmentioning

confidence: 99%

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Compton Imaging and Machine-Learning techniques for an enhanced sensitivity in key stellar (n,γ) measurements

et al. 2022

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Neutron capture cross-section measurements are fundamental in the study of astrophysical phenomena, such as the slow neutron capture (s-) process of nucleosynthesis operating in red-giant stars. To enhance the sensitivity of such measurements we have developed the i-TED detector. i-TED is an innovative detection system which exploits the Compton imaging technique with the aim of obtaining information about the incoming direction of the detected γ-rays. The imaging capability allows one to reject a large fraction of the dominant γ-ray background, hence enhancing the (n,γ) detection sensitivity. This work summarizes the main results of the first experimental proof-of-concept of the background rejection with i-TED carried out at CERN n_TOF using an early i-TED demonstrator. Two state-of-the-art C6D6 detectors were also used to benchmark the performance of i-TED. The i-TED prototype built for this study shows a factor of ~3 higher detection sensitivity than C6D6 detectors in the ~10 keV neutron-energy range of astrophysical interest. This works also introduces the perspectives of further enhancement in performance attainable with the final i-TED array and new analysis methodologies based on Machine-Learning techniques. The latter provide higher (n,γ) detection efficiency and similar enhancement in the sensitivity than the analytical method based on the Compton scattering law. Finally, we present our proposal to use this detection system for the first time on key astrophysical (n,γ) measurements, in particular on the s-process branching-point 79Se, which is especially well suited to constrain the thermal conditions of Red Giant and Massive Stars.

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Section: Compton Imaging For Background Rejection: Proof-of-conceptmentioning

confidence: 99%

“…The details on the technical implementation of the i-TED detector, displayed in Figure 3, are given in Refs. [8,9].…”

Section: Prospects Based On Machine Learning Techniquesmentioning

confidence: 99%

Compton Imaging and Machine-Learning techniques for an enhanced sensitivity in key stellar (n,γ) measurements

et al. 2022

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“…A detailed description of the first such i-TED module can be found in Ref. 40 . i-TED features an excellent time resolution for enabling the TOF technique 39 and it has been especially designed to attain a high detection efficiency, a low sensitivity to scattered-neutron backgrounds and a high image resolving power.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…While the work presented here is entirely based on Monte-Carlo (MC) simulations, the i-TED detector has been already developed 34,38,[40][41][42] and employed for TOF experiments at CERN n_TOF 39 . Therefore, intrinsic performance parameters such as energy resolution 41 , 3D intrinsic position resolution 34,42 and efficiency 40 have been experimentally validated and are realistically included in the present study. Based on our previous extensive experience in MC simulations of detectors 38,39 and neutron production and transport 43 , in the present simulation work we have been able to account for both geometrical and physical effects to a great level of detail.…”

Section: Introductionmentioning

confidence: 99%

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Towards machine learning aided real-time range imaging in proton therapy

Lerendegui-Marco¹,

Balibrea-Correa²,

Babiano-Súarez³

et al. 2022

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Compton imaging represents a promising technique for range verification in proton therapy treatments. In this work, we report on the advantageous aspects of the i-TED detector for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that have been specifically designed for neutron-capture nuclear physics experiments, which are characterized by γ-ray energies spanning up to 5-6 MeV, rather low γ-ray emission yields and very intense neutron induced γ-ray backgrounds. Our developments to cope with these three aspects are concomitant with those required in the field of hadron therapy, especially in terms of high efficiency for real-time monitoring, low sensitivity to neutron backgrounds and reliable performance at the high γ-ray energies. We find that signal-to-background ratios can be appreciably improved with i-TED thanks to its light-weight design and the low neutron-capture cross sections of its LaCl 3 crystals, when compared to other similar systems based on LYSO, CdZnTe or LaBr 3 . Its high time-resolution (CRT∼500 ps) represents an additional advantage for background suppression when operated in pulsed HT mode. Each i-TED Compton module features two detection planes of very large LaCl 3 monolithic crystals, thereby achieving a high efficiency in coincidence of 0.2% for a point-like 1 MeV γ-ray source at 5 cm distance. This leads to sufficient statistics for reliable image reconstruction with an array of four i-TED detectors assuming clinical intensities of 10 8 protons per treatment point. The use of a two-plane design instead of three-planes has been preferred owing to the higher attainable efficiency for double time-coincidences than for threefold events. The loss of full-energy events for high energy γ-rays is compensated by means of Machine-Learning based algorithms, which allow one to enhance the signal-to-total ratio up to a factor of 2.

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Background study for(n,γ)cross section measurements with C6D
Ren
¹
,
Ruan
²
,
Jiang
³

et al. 2021
Nuclear Instruments and Methods in Physics Research Section A:

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First i-TED demonstrator: A Compton imager with Dynamic Electronic Collimation

Cited by 28 publications

References 52 publications

Compton Imaging and Machine-Learning techniques for an enhanced sensitivity in key stellar (n,γ) measurements

Compton Imaging and Machine-Learning techniques for an enhanced sensitivity in key stellar (n,γ) measurements

Towards machine learning aided real-time range imaging in proton therapy

Background study for(n,γ)cross section measurements with C6D
Ren
¹
,
Ruan
²
,
Jiang
³

et al. 2021
Nuclear Instruments and Methods in Physics Research Section A:

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First i-TED demonstrator: A Compton imager with Dynamic Electronic Collimation

Cited by 28 publications

References 52 publications

Compton Imaging and Machine-Learning techniques for an enhanced sensitivity in key stellar (n,γ) measurements

Compton Imaging and Machine-Learning techniques for an enhanced sensitivity in key stellar (n,γ) measurements

Towards machine learning aided real-time range imaging in proton therapy

Background study for(n,γ)cross section measurements with C6DRen1, Ruan2, Jiang3 et al. 2021Nuclear Instruments and Methods in Physics Research Section A:

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Resources

About

Background study for(n,γ)cross section measurements with C6D
Ren
¹
,
Ruan
²
,
Jiang
³

et al. 2021
Nuclear Instruments and Methods in Physics Research Section A: