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Assessment of Dose Reduction Strategies in Wavelength-Selective Neutron Tomography

Published

Author(s)

Daniel Hussey, Peter Bajcsy, Paul A. Kienzle, Jacob LaManna, David Jacobson, Victoria DiStefano, Daniel Pelt, James Sethian

Abstract

The goal of this study is to determine variable relationships and a computational workflow that yield the highest quality of three-dimensional reconstructions in neutron imaging applications with reduced number of projections angles. Neutrons interact with matter primarily through the strong nuclear force providing unique image contrast modes. Accessing many of these contrast modes requires defining the energy of the neutron beam, resulting in long exposure times for a single two-dimensional projection image. To collect of order 100 tomograms at different neutron wavelengths within a reasonable time frame (less than 1 week) suggests the use of dose reduction tomography reconstruction algorithms. We identified and evaluated the main factors affecting the quality of the 3D tomographic reconstruction in the computational image workflow: the projection number, the reconstruction method, and the post-processing method. This study reports several relationships between 3D reconstruction quality metrics and acquisition time. Based on the established relationships, the performance of a seeded simultaneous iterative reconstruction technique (SIRT) yielded improved image quality and more accurate estimates of the reconstructed attenuation values compared to a SIRT without a priori information or a trained neural network based on a mixed scale dense network.
Proceedings Title
2nd International Conference on Image Processing and Vision Engineering (IMPROVE 2022)
Conference Dates
April 22-24, 2022
Conference Location
Online, MD, US

Keywords

3D reconstruction image quality, dose reduction, neutron imaging.

Citation

Hussey, D. , Bajcsy, P. , Kienzle, P. , LaManna, J. , Jacobson, D. , DiStefano, V. , Pelt, D. and Sethian, J. (2023), Assessment of Dose Reduction Strategies in Wavelength-Selective Neutron Tomography, 2nd International Conference on Image Processing and Vision Engineering (IMPROVE 2022), Online, MD, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934103 (Accessed December 12, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created July 31, 2023, Updated November 21, 2024