Compton 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
AIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité,
2 École des Ponts ParisTech, Champs-sur-Marne, France
3 CEA, LIST, Sensors and Electronic Architectures Laboratory, Gif-sur-Yvette, France
Published online: 20 January 2020
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.
Key words: Compton imaging / SOE / Bayes / Caliste / Compton inversion
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.