Reconstructing the Position and Intensity of Multiple Gamma-Ray Point Sources with a Sparse Parametric Algorithm

Autor: Vavrek, Jayson R., Hellfeld, Daniel, Bandstra, Mark S., Negut, Victor, Meehan, Kathryn, Vanderlip, William J., Cates, Joshua W., Pavlovsky, Ryan, Quiter, Brian J., Cooper, Reynold J., Joshi, Tenzing H. Y.
Rok vydání: 2020
Předmět:
Druh dokumentu: Working Paper
DOI: 10.1109/TNS.2020.3024735
Popis: We present an experimental demonstration of Additive Point Source Localization (APSL), a sparse parametric imaging algorithm that reconstructs the 3D positions and activities of multiple gamma-ray point sources. Using a handheld gamma-ray detector array and up to four $8$ ${\mu}$Ci $^{137}$Cs gamma-ray sources, we performed both source-search and source-separation experiments in an indoor laboratory environment. In the majority of the source-search measurements, APSL reconstructed the correct number of sources with position accuracies of ${\sim}20$ cm and activity accuracies (unsigned) of ${\sim}20\%$, given measurement times of two to three minutes and distances of closest approach (to any source) of ${\sim}20$ cm. In source-separation measurements where the detector could be moved freely about the environment, APSL was able to resolve two sources separated by $75$ cm or more given only ${\sim}60$ s of measurement time. In these source-separation measurements, APSL produced larger total activity errors of ${\sim}40\%$, but obtained source separation distances accurate to within $15$ cm. We also compare our APSL results against traditional Maximum Likelihood-Expectation Maximization (ML-EM) reconstructions, and demonstrate improved image accuracy and interpretability using APSL over ML-EM. These results indicate that APSL is capable of accurately reconstructing gamma-ray source positions and activities using measurements from existing detector hardware.
Comment: 10 pages, 9 figures. Accepted for publication at IEEE Transactions on Nuclear Science
Databáze: arXiv
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