Assessment of Dose-Reduction Strategies in Wavelength-Selective Neutron Tomography

Abstract This study aims to determine an acquisitional and computational workflow that yields the highest quality spatio-spectral reconstructions in four-dimensional neutron tomography studies. The properties of neutrons enable unique image contrast modes, but accessing these modes requires defining energy beam, resulting long acquisition times. We seek sparse angular approaches collect order 100 tomograms at different wavelengths using minimum number input projection images. In workflows, we identified evaluated main factors affecting tomographic reconstruction such as number, method, post-processing method report relationships between 3D metrics time. Based on relationships, performance seeded simultaneous iterative reconstruction-based techniques (SIRT SIRT with total variation regularization) yielded improved more accurate estimates reconstructed attenuation values compared other methods, which included convolutional neural networks. methods were then applied a dose-reduced monochromatic dataset characterized via signal-to-noise ratio (SNR) single-voxel resolution.