Enhanced use of contextual data for quantitative Compton imaging

Contextual sensors can be equipped to radiation detection systems to allow free-moving 3D gamma-ray imaging through scene data fusion. Scene data fusion captures relevant scene information to construct a 3D map of an environment, which can be used to constrain image reconstruction techniques. While developed to enable free-moving imaging measurements, scene data fusion also has applications in cases that require multiple static measurements to generate 3D images, where the scene information can improve results. One way we seek to further leverage contextual scene information is to use the 3D map to automatically identify the radiological object of interest in a scene, and then determine optimal measurement poses around that object for quantitative Compton imaging. We also seek to improve the use of contextual information by identifying materials present in an environment to inform attenuation estimates for intervening materials. We present the approach for further leveraging the contextual information, and the preliminary results of using an SDF-enabled gamma-ray imager to find optimal measurement positions for a distributed source scenario to produce quantitative Compton images with minimization of associated uncertainties.