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Ongoing advancement of free-moving radiation imaging and mapping

Brian J. Quiter, Mark S. Bandstra, Joshua W. Cates, R.J. Cooper, Joseph C. Curtis, Daniel Hellfeld, Tenzing H. Y. Joshi, Ryan Pavlovsky, E. Rofors, M. Salathe, Jayson R. Vavrek, K. Vetter

发表年份
2022
引用次数
2

摘要

By combining radiation detection technologies with robotics sensing, the ability to continuously conduct gamma-ray imaging using freely-moving systems was demonstrated in 2015.<sup>1</sup> This new method, which was named free-moving 3D Scene Data Fusion (SDF), was then applied to mapping radioactive contamination and to contextualizing the extent of contamination and the efficacy of radiological clean-up efforts.<sup>2, 3</sup> Since then, further studies into the types of radiation detection systems to which SDF could be applied resulted in the discovery and demonstration that neutron activity could be mapped using neutron-sensitive CLLBC scintillators, arrays of pixelated CZT detectors could be used to create multi-modal imagers, and more rudimentary detector systems such as arrays of four CsI modules could still achieve good-quality mapping by inferring source positioning through the encoded modulation of source-to-detector distance. This paper provides an overview of the SDF technology, highlights recent measurements leveraging SDF-equipped systems, discusses the continued development of quantitative algorithms<sup>4, 5</sup> and their ramifications for developing autonomous SDF-capabilities, and summarizes future directions of research and application development for free moving radiation detection systems.

关键词

DetectorComputer scienceScintillatorParticle detectorRadiationArtificial intelligencePhysicsOpticsTelecommunications

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