Open AccessCompton imaging reconstruction methods: a comparative performance study of direct back-projection, SOE, a new Bayesian algorithm and a new Compton inversion method applied to real data with Caliste
Author(s) -
Geoffrey Daniel,
O. Limousin,
Daniel Maier,
A. Meuris,
F. Carrel
Publication year - 2020
Publication title -
epj web of conferences
Language(s) - English
Resource type - Journals
eISSN - 2101-6275
pISSN - 2100-014X
DOI - 10.1051/epjconf/202022506006
Subject(s) - detector , physics , compton scattering , photon , projection (relational algebra) , optics , bayesian probability , algorithm , computer science , artificial intelligence
Compton imaging is one of the main methods to localize radioactive hotspots, which emit high-energy gamma-ray photons, above 200 keV. Most of the Compton imaging systems are composed by at least two detection layers or one 3D position sensitive detector. In this study, we demonstrate the application of a new miniature pixelated single plane detector to Compton imaging. In this configuration, we do not have the information on interaction depth but we successfully test its ability to perform Compton localization by means of comparing different Compton reconstruction algorithms applied to real data measured with our single plane detection system.