On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source
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 simpl...
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doaj-8850866ce1f84ad18dbbfd5533b752632020-11-25T02:58:09ZengMDPI AGJournal of Imaging2313-433X2020-05-016353510.3390/jimaging6050035On a Method For Reconstructing Computed Tomography Datasets from an Unstable SourceNicholas Stull0Josh McCumber1Lawrence D'Aries2Michelle Espy3Cort Gautier4James Hunter5Los Alamos National Laboratory, Los Alamos, NM 87545, USAPhoenix, LLC., Monona, WI 53713, USAUS Army CCDC-Armaments Center, Picatinny Arsenal, NJ 07806, USALos Alamos National Laboratory, Los Alamos, NM 87545, USALos Alamos National Laboratory, Los Alamos, NM 87545, USALos Alamos National Laboratory, Los Alamos, NM 87545, USAAs 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.https://www.mdpi.com/2313-433X/6/5/35neutron radiographycomputed tomographyimage processing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nicholas Stull Josh McCumber Lawrence D'Aries Michelle Espy Cort Gautier James Hunter |
spellingShingle |
Nicholas Stull Josh McCumber Lawrence D'Aries Michelle Espy Cort Gautier James Hunter On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source Journal of Imaging neutron radiography computed tomography image processing |
author_facet |
Nicholas Stull Josh McCumber Lawrence D'Aries Michelle Espy Cort Gautier James Hunter |
author_sort |
Nicholas Stull |
title |
On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source |
title_short |
On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source |
title_full |
On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source |
title_fullStr |
On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source |
title_full_unstemmed |
On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source |
title_sort |
on a method for reconstructing computed tomography datasets from an unstable source |
publisher |
MDPI AG |
series |
Journal of Imaging |
issn |
2313-433X |
publishDate |
2020-05-01 |
description |
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. |
topic |
neutron radiography computed tomography image processing |
url |
https://www.mdpi.com/2313-433X/6/5/35 |
work_keys_str_mv |
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