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Thilo Balke, Alexander M. Long, Sven C. Vogel, Brendt Wohlberg and Charles A. Bouman, "Hyperspectral Neutron CT with Material Decomposition", in Proceedings of IEEE International Conference on Image Processing (ICIP), (Anchorage, AK, USA), doi:10.1109/ICIP42928.2021.9506080, Sep 2021

Abstract

Energy resolved neutron imaging (ERNI) is an advanced neutron radiography technique capable of non-destructively extracting spatial isotopic information within a given material. Energy-dependent radiography image sequences can be created by utilizing neutron time-of-flight techniques. In combination with uniquely characteristic isotopic neutron cross-section spectra, isotopic areal densities can be determined on a per-pixel basis, thus resulting in a set of areal density images for each isotope present in the sample. By preforming ERNI measurements over several rotational views, an isotope decomposed D computed tomograpy is possible.We demonstrate a method involving a robust and automated background estimation based on a linear programming formulation. The extremely high noise due to low count measurements is overcome using a sparse coding approach. It allows for a significant computation time improvement, from weeks to a few hours compared to existing neutron evaluation tools, enabling at the present stage a semi-quantitative, user-friendly routine application.

BibTeX Entry

@inproceedings{balke-2021-hyperspectral,
author = {Thilo Balke and Alexander M. Long and Sven C. Vogel and Brendt Wohlberg and Charles A. Bouman},
title = {Hyperspectral Neutron {CT} with Material Decomposition},
year = {2021},
month = Sep,
urlpdf = {http://engineering.purdue.edu/~bouman/publications/orig-pdf/2021-icip-Thilo.pdf},
booktitle = {Proceedings of IEEE International Conference on Image Processing (ICIP)},
address = {Anchorage, AK, USA},
doi = {10.1109/ICIP42928.2021.9506080}
}