MLEM-based image reconstruction algorithm for fast neutron scattering imaging

Abstract Fast neutrons preserve the initial source information (e.g., position, energy, and time) due to their relatively low probability of interaction with surrounding materials and their straight path. When measuring fast neutrons using scattering reactions, there is no need to slow them down to thermal neutrons. This allows for the obtainment of more accurate information. A neutron scattering imager usually consists of two pixelated scatter detectors. The energy and scattering angle of the neutrons can be determined from the energy of the protons produced by the scattering reaction in the first detector, the time of flight between the two detectors, and the distance between the interaction positions. From these measured quantities, conical surfaces can be drawn, and the source location can be determined roughly from the overlapping of all such surfaces drawn. Maximum Likelihood Expectation Maximization (MLEM) is an iterative statistical algorithm to reconstruct the source distribution from the measured events in the neutron scattering imager. In this study, we developed an MLEM algorithm for fast neutron (≤ 20 MeV) scattering image reconstruction using a system matrix with consideration of the scattering cross-section and angular resolution. Then, we compared the resolution of the MLEM images with that of simple back-projection (SBP) images.