Evaluation of Few-View Reconstruction Parameters for Illicit Substance Detection using Fast-Neutron Transmission Spectroscopy

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Fink, C. L
Humm, P. G
Micklich, B. J
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We have evaluated the performance of an illicit substance detection system that performs image reconstruction using the Maximum Likelihood algebraic reconstruction algorithm, a few number of projections, and relatively coarse projection and pixel resolution. This evaluation was done using receiver operator curves and simulated data from the fast-neutron transmission spectroscopy system operated in a mode to detect explosives in luggage. The results show that increasing the number of projection angles is more important than increasing the projection resolution, the reconstructed pixel resolution, or the number of iterations in the Maximum Likelihood algorithm. A 100% detection efficiency with essentially no false positives is possible for a square block of RDX explosive, a projection resolution of 2 cm, a reconstructed pixel size of 2x2 cm, and five projection angles. For rectangular shaped explosives more angles are required to obtain the same system performance.

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1996-06-01
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Copyright 1996 IEEE. Reprinted from IEEE Transactions on Nuclear Science, Volume 43, Issue 3, June 1996, pages 1352-1356. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. NOTE: At the time of publication, the author was affiliated with Argonne National Laboratory. Currently March 2007, he is a faculty member of the Department of Computer and Information Sciences at the University of Pennsylvania.
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