Skip to main content
Open Access Publications from the University of California

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

  • Author(s): Vavrek, JR;
  • Hellfeld, D;
  • Bandstra, MS;
  • Negut, V;
  • Meehan, K;
  • Vanderlip, WJ;
  • Cates, JW;
  • Pavlovsky, R;
  • Quiter, BJ;
  • Cooper, RJ;
  • Joshi, THY
  • et al.

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.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View