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

TL;DR

This paper demonstrates a sparse parametric algorithm, APSL, for accurately localizing and quantifying multiple gamma-ray sources in 3D using handheld detectors, outperforming traditional methods in accuracy and interpretability.

Contribution

The paper introduces APSL, a novel sparse parametric imaging algorithm for 3D gamma-ray source localization and activity estimation, validated through experimental indoor tests.

Findings

APSL accurately localizes sources within ~20 cm in position.

APSL estimates source activities with ~20% accuracy.

APSL outperforms traditional ML-EM in image accuracy and interpretability.

Abstract

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.