
Proceedings Paper
Acceleration of iterative image reconstruction for x-ray imaging for security applicationsFormat | Member Price | Non-Member Price |
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Paper Abstract
Three-dimensional image reconstruction for scanning baggage in security applications is becoming
increasingly
important. Compared to medical x-ray imaging, security imaging systems must be designed for a
greater variety of objects. There is a lot of variation in attenuation and nearly every bag scanned
has metal present, potentially yielding significant artifacts. Statistical iterative reconstruction
algorithms are known to reduce metal artifacts and yield quantitatively more accurate estimates of
attenuation than linear methods.
For iterative image reconstruction algorithms to be deployed at security checkpoints, the images
must be quantitatively accurate and the convergence speed must be increased dramatically. There are
many approaches for increasing convergence; two approaches are described in detail in this paper.
The first approach includes a scheduled change in the number of ordered subsets over iterations and
a reformulation of convergent ordered subsets that was originally proposed by Ahn, Fessler et. al.1
The second approach is based on varying the multiplication factor in front of the additive step in
the alternating minimization (AM) algorithm, resulting in
more aggressive updates in iterations. Each approach is implemented on real data from a SureScanTM
x 1000 Explosive Detection System∗ and compared to straightforward implementations of the
alternating minimization
algorithm of O’Sullivan and Benac2 with a Huber-type edge-preserving penalty, originally proposed
by Lange.3
Paper Details
Date Published: 12 March 2015
PDF: 15 pages
Proc. SPIE 9401, Computational Imaging XIII, 94010C (12 March 2015); doi: 10.1117/12.2082966
Published in SPIE Proceedings Vol. 9401:
Computational Imaging XIII
Charles A. Bouman; Ken D. Sauer, Editor(s)
PDF: 15 pages
Proc. SPIE 9401, Computational Imaging XIII, 94010C (12 March 2015); doi: 10.1117/12.2082966
Show Author Affiliations
Soysal Degirmenci, Washington Univ. in St. Louis (United States)
David G. Politte, Washington Univ. in St. Louis (United States)
Carl Bosch, SureScan Corp. (United States)
David G. Politte, Washington Univ. in St. Louis (United States)
Carl Bosch, SureScan Corp. (United States)
Nawfel Tricha, SureScan Corp. (United States)
Joseph A. O'Sullivan, Washington Univ. in St. Louis (United States)
Joseph A. O'Sullivan, Washington Univ. in St. Louis (United States)
Published in SPIE Proceedings Vol. 9401:
Computational Imaging XIII
Charles A. Bouman; Ken D. Sauer, Editor(s)
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