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Recent Advances in Radiation Detection and Imaging Systems

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Prof. Dr. Kai Vetter

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1. Department of Nuclear Engineering, University of California, Berkeley, Berkeley, CA 94720, USA
2. Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Interests: nuclear physics; radiation detection, nuclear instrumentation and measuerements; multi-sensor systems and data fusion; radiological resilience
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Dear Colleagues,

Radiation detection and imaging systems provide a means to study phenomena and processes ranging from the smallest to the largest scales known to us; they allow us to look into the structure and composition of atomic nuclei at the smallest scales as well as the formation of matter and stars at the largest scales. They provide means to visualize processes in the human body, to understand, prevent, and cure diseases, to ensure the safety and security of nuclear materials and facilities, to prevent the proliferation of illicit materials, to respond to emergencies, or to map the elemental composition of the surface of our Earth or other planets and objects in our solar system. Recent advances in radiation detection and imaging concepts enable enormous gains in sensitivity and resolution, providing unprecedented ways of elucidating these wide-ranging phenomena and processes. They are based on the continuing developments in radiation detection materials and their implementations, signal readouts and processing methodologies and technologies, as well as the capabilities of computing and data analytics. In many circumstances, these advances are complemented by the enormous progress in utilizing complementary sensor technologies, the fusion of the complementary data, and the availability of new machine learning methodologies.

This Special Issue aims to cover important aspects in these developments, driven by the challenges and opportunities in different fields underpinned by the technological advances in radiation detection and imaging.

Prof. Dr. Kai Vetter
Guest Editor

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Keywords

radiation detection concepts and technologies
radiation imaging
particle detection and tracking
gamma-ray imagers and telescopes
neutron detection and imaging
radiation detection materials
readouts and signal processing
multi-sensor networks and data fusion
data analytics, machine learning, and artificial intelligence

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Research

24 pages, 13034 KiB

Open AccessArticle

Fast and Accurate Gamma Imaging System Calibration Based on Deep Denoising Networks and Self-Adaptive Data Clustering

by Yihang Zhu, Zhenlei Lyu, Wenzhuo Lu, Yaqiang Liu and Tianyu Ma

Sensors 2023, 23(5), 2689; https://doi.org/10.3390/s23052689 - 1 Mar 2023

Viewed by 1667

Abstract

Gamma imagers play a key role in both industrial and medical applications. Modern gamma imagers typically employ iterative reconstruction methods in which the system matrix (SM) is a key component to obtain high-quality images. An accurate SM could be acquired from an experimental calibration step with a point source across the FOV, but at a cost of long calibration time to suppress noise, posing challenges to real-world applications. In this work, we propose a time-efficient SM calibration approach for a 4π-view gamma imager with short-time measured SM and deep-learning-based denoising. The key steps include decomposing the SM into multiple detector response function (DRF) images, categorizing DRFs into multiple groups with a self-adaptive K-means clustering method to address sensitivity discrepancy, and independently training separate denoising deep networks for each DRF group. We investigate two denoising networks and compare them against a conventional Gaussian filtering method. The results demonstrate that the denoised SM with deep networks faithfully yields a comparable imaging performance with the long-time measured SM. The SM calibration time is reduced from 1.4 h to 8 min. We conclude that the proposed SM denoising approach is promising and effective in enhancing the productivity of the 4π-view gamma imager, and it is also generally applicable to other imaging systems that require an experimental calibration step. Full article

(This article belongs to the Special Issue Recent Advances in Radiation Detection and Imaging Systems)

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15 pages, 5869 KiB

Open AccessArticle

A Wide Energy Range and 4π-View Gamma Camera with Interspaced Position-Sensitive Scintillator Array and Embedded Heavy Metal Bars

by Yifan Hu, Zhenlei Lyu, Peng Fan, Tianpeng Xu, Shi Wang, Yaqiang Liu and Tianyu Ma

Sensors 2023, 23(2), 953; https://doi.org/10.3390/s23020953 - 13 Jan 2023

Cited by 5 | Viewed by 1946

Abstract

(1) Background: Gamma cameras have wide applications in industry, including nuclear power plant monitoring, emergency response, and homeland security. The desirable properties of a gamma camera include small weight, good resolution, large field of view (FOV), and wide imageable source energy range. Compton cameras can have a 4π FOV but have limited sensitivity at low energy. Coded-aperture gamma cameras are operatable at a wide photon energy range but typically have a limited FOV and increased weight due to the thick heavy metal collimators and shielding. In our lab, we previously proposed a 4π-view gamma imaging approach with a 3D position-sensitive detector, with which each detector element acts as the collimator for other detector elements. We presented promising imaging performance for ^99mTc, ¹⁸F, and ¹³⁷Cs sources. However, the imaging performance for middle- and high-energy sources requires further improvement. (2) Methods: In this study, we present a new gamma camera design to achieve satisfactory imaging performance in a wide gamma energy range. The proposed gamma camera consists of interspaced bar-shaped GAGG (Ce) crystals and tungsten absorbers. The metal bars enhance collimation for high-energy gamma photons without sacrificing the FOV. We assembled a gamma camera prototype and conducted experiments to evaluate the gamma camera’s performance for imaging ⁵⁷Co, ¹³⁷Cs, and ⁶⁰Co point sources. (3) Results: Results show that the proposed gamma camera achieves a positioning accuracy of <3° for all gamma energies. It can clearly resolve two ¹³⁷Cs point sources with 10° separation, two ⁵⁷Co and two ⁶⁰Co point sources with 20° separation, as well as a 2 × 3 ¹³⁷Cs point-source array with 20° separation. (4) Conclusions: We conclude that the proposed gamma camera design has comprehensive merits, including portability, 4π-view FOV, and good angular resolution across a wide energy range. The presented approach has promising potential in nuclear security applications. Full article

(This article belongs to the Special Issue Recent Advances in Radiation Detection and Imaging Systems)

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