Fast Hyperspectral Neutron Tomography

Journal Article · Thu May 01 00:00:00 EDT 2025 · IEEE Transactions on Computational Imaging

DOI:https://doi.org/10.1109/TCI.2025.3567854· OSTI ID:2572194

Chowdhury, Mohammad Samin Nur ^[1]; Yang, Diyu ^[1]; Tang, Shimin ^[2]; Singanallur Vaidyanathan, Venkatakrishnan ^[2]; Bilheux, Hassina ^[2]; Buzzard, Gregery T ^[1]; Bouman, Charles ^[1]

---

1. Purdue University
2. ORNL

Hyperspectral neutron computed tomography is a tomographic imaging technique in which thousands of wavelength-specific neutron radiographs are measured for each tomographic view. In conventional hyperspectral reconstruction, data from each neutron wavelength bin are reconstructed separately, which is extremely time-consuming. These reconstructions often suffer from poor quality due to low signal-to-noise ratios. Consequently, material decomposition based on these reconstructions tends to produce inaccurate estimates of the material spectra and erroneous volumetric material separation. In this paper, we present two novel algorithms for processing hyperspectral neutron data: fast hyperspectral reconstruction and fast material decomposition. Both algorithms rely on a subspace decomposition procedure that transforms hyperspectral views into low-dimensional projection views within an intermediate subspace, where tomographic reconstruction is performed. The use of subspace decomposition dramatically reduces reconstruction time while reducing both noise and reconstruction artifacts. We apply our algorithms to both simulated and measured neutron data and demonstrate that they reduce computation and improve the quality of the results relative to conventional methods.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE; USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 2572194
• Journal Information: IEEE Transactions on Computational Imaging, Journal Name: IEEE Transactions on Computational Imaging Vol. 11
• Country of Publication: United States
• Language: English