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Scientific Publication Citing Dragonfly

On a method for reconstructing computed tomography datasets from an unstable source

Nicholas Stull(1), Josh McCumber(2), Lawrence D’Aries(3), Michelle Espy(1), Cort Gautier(1), James Hunter(1)
Journal of Imaging, 6, Issue 5, May 2020: 35. DOI: 10.3390/jimaging6050035

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Keywords

neutron radiography, computed tomography, image processing

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Abstract

As work continues in neutron computed tomography, at Los Alamos Neutron Science Center (LANSCE) and other locations, source reliability over the long imaging times is an issue of increasing importance. Moreover, given the time commitment involved in a single neutron image, it is impractical to simply discard a scan and restart in the event of beam instability. In order to mitigate the cost and time associated with these options, strategies are presented in the current work to produce a successful reconstruction of computed tomography data from an unstable source. The present work uses a high energy neutron tomography dataset from a simulated munition collected at LANSCE to demonstrate the method, which is general enough to be of use in conjunction with unstable X-ray computed tomography sources as well.

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How Our Software Was Used

Dragonfly was used for the reconstruction of a high energy neutron radiography CT dataset.

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Author Affiliation

(1) Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
(2) Phoenix, LLC., Monona, WI 53713, USA.
(3) US Army CCDC-Armaments Center, Picatinny Arsenal, NJ 07806, USA.

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