We present an experimental demonstration of additive point source localization (APSL), a sparse parametric imaging algorithm that reconstructs the 3-D positions and activities of multiple gamma-ray point sources. Using a handheld gamma-ray detector array and up to four 8 $\mu $ Ci 137Cs 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 ~20 cm and activity accuracies (unsigned) of ~20%, given measurement times of 2 to 3 min and distances of closest approach (to any source) of ~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 ~60 s of measurement time. In these source-separation measurements, APSL produced larger total activity errors of ~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.

中文翻译：

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用稀疏参数算法重建多个伽马射线点源的位置和强度

我们提出了加性点源定位 (APSL) 的实验演示，这是一种稀疏参数成像算法，可重建多个伽马射线点源的 3-D 位置和活动。使用手持式伽马射线探测器阵列和多达四个 8 $\mu $ Ci 137Cs 伽马射线源，我们在室内实验室环境中进行了源搜索和源分离实验。在大多数源搜索测量中，APSL 重建了正确数量的源，其位置精度为 ~20 cm，活动精度（无符号）为 ~20%，给定的测量时间为 2 到 3 分钟，距离最近（至任何来源）约 20 厘米。在检测器可以在环境中自由移动的源分离测量中，APSL 能够解析相距 75 cm 或更多的两个源，只要大约 60 s 的测量时间。在这些源分离测量中，APSL 产生了更大的约 40% 的总活动误差，但获得的源分离距离精确到 15 厘米以内。我们还将我们的 APSL 结果与传统的最大似然期望最大化 (ML-EM) 重建进行比较，并证明使用 APSL 比 ML-EM 提高了图像准确性和可解释性。这些结果表明 APSL 能够使用现有探测器硬件的测量值准确地重建伽马射线源的位置和活动。我们还将我们的 APSL 结果与传统的最大似然期望最大化 (ML-EM) 重建进行比较，并证明使用 APSL 比 ML-EM 提高了图像准确性和可解释性。这些结果表明 APSL 能够使用现有探测器硬件的测量值准确地重建伽马射线源的位置和活动。我们还将我们的 APSL 结果与传统的最大似然期望最大化 (ML-EM) 重建进行比较，并证明使用 APSL 比 ML-EM 提高了图像准确性和可解释性。这些结果表明 APSL 能够使用现有探测器硬件的测量值准确地重建伽马射线源的位置和活动。