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Iterative Reconstruction for Multimodal Neutron Tomography

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We describe a unified framework for model-based iterative 3-D reconstruction of multimodal neutron transmission, hydrogen-scatter, and induced-fission images from low resolution data recorded using $\mathrm {14.1~\!\!\text {-}\text{MeV} }$ neutrons and the associated-particle imaging (API) technique. The framework, which was developed to facilitate use in challenging field-deployment scenarios, is centered around physics-based system models and a total variation (TV) constrained implementation of the simultaneous iterative reconstruction technique (SIRT). Modified to solve a statistically weighted least squares (WLS) problem, the SIRT algorithm is accelerated using ordered subsets and Nesterov’s momentum for which we derive a near-optimal value of the governing Lipschitz constant. The approach enables the reconstruction of images that are high resolution compared to the acquired data and is robust to both limited statistics and a limited number of projection angles. Moreover, the framework is fast enough to be practical. Example images are provided that demonstrate both the ability to perform fast-neutron imaging of high-atomic-number materials with low radiation dose and the benefit of multimodal neutron imaging to identify key materials.

NeutronsImagingDetectorsImage reconstructionTomographyHydrogenIterative methodsAttenuationThree-dimensional displaysRadiography

Jens Gregor、Matthew R. Heath、Timothy Deller、Matthew A. Blackston、Paul Hausladen

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Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN, USA

Oak Ridge National Laboratory, Oak Ridge, TN, USA

Oak Ridge National Laboratory, Oak Ridge, TN, USA|Leidos, Oak Ridge, TN, USA

2025

IEEE transactions on nuclear science

IEEE transactions on nuclear science

ISSN:
年,卷(期):2025.72(5)
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