Scene-Informed Optimization of Measurement Locations for Radiological Assessment

Published in 2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2022

Recommended citation: K. Knecht et. al., "Scene-Informed Optimization of Measurement Locations for Radiological Assessment," in Proc. NSS/MIC, 2022.

Portable radiation detection systems can be equipped with contextual sensors to allow free-moving 3D gamma-ray imaging in a method called scene data fusion (SDF). The scene information provided by the contextual sensors can be used to enable 3D imaging and constrain image reconstruction to improve imaging accuracy and computational efficiency.

While developed for free-moving measurements, SDF also has applications in cases that require multiple static measurements to generate 3D images, where the scene information can improve results. The scene information captured by these devices can be leveraged to determine optimal measurement positions for quantification measurements, such as in safeguards applications, where limited time is provided to quantify nuclear material present. In this work we are utilizing the 3D scene information obtained from an initial survey to create a measurement space that allows the determination of optimal positions and orientations (pose) of an instrument to assess radiological materials of interest. We will present our approach and results for performing an optimization to quantify properties of interest in low count rate environments and the minimization of associated uncertainties.

Recommended citation: K. Knecht et. al., “Scene-Informed Optimization of Measurement Locations for Radiological Assessment,” 2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).