Share Email Print

Proceedings Paper

Adaptive x-ray threat detection using sequential hypotheses testing with fan-beam experimental data (Conference Presentation)
Author(s): Ratchaneekorn Thamvichai; Liang-Chih Huang; Amit Ashok; Qian Gong; David Coccarelli; Joel A. Greenberg; Michael E. Gehm; Mark A. Neifeld

Paper Abstract

We employ an adaptive measurement system, based on sequential hypotheses testing (SHT) framework, for detecting material-based threats using experimental data acquired on an X-ray experimental testbed system. This testbed employs 45-degree fan-beam geometry and 15 views over a 180-degree span to generate energy sensitive X-ray projection data. Using this testbed system, we acquire multiple view projection data for 200 bags. We consider an adaptive measurement design where the X-ray projection measurements are acquired in a sequential manner and the adaptation occurs through the choice of the optimal "next" source/view system parameter. Our analysis of such an adaptive measurement design using the experimental data demonstrates a 3x-7x reduction in the probability of error relative to a static measurement design. Here the static measurement design refers to the operational system baseline that corresponds to a sequential measurement using all the available sources/views. We also show that by using adaptive measurements it is possible to reduce the number of sources/views by nearly 50% compared a system that relies on static measurements.

Paper Details

Date Published: 7 June 2017
PDF: 1 pages
Proc. SPIE 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II, 101870A (7 June 2017); doi: 10.1117/12.2266756
Show Author Affiliations
Ratchaneekorn Thamvichai, The Univ. of Arizona (United States)
Liang-Chih Huang, The Univ. of Arizona (United States)
Amit Ashok, College of Optical Sciences, The Univ. of Arizona (United States)
Qian Gong, Duke Univ. (United States)
David Coccarelli, Duke Univ. (United States)
Joel A. Greenberg, Duke Univ. (United States)
Michael E. Gehm, Duke Univ. (United States)
Mark A. Neifeld, The Univ. of Arizona (United States)

Published in SPIE Proceedings Vol. 10187:
Anomaly Detection and Imaging with X-Rays (ADIX) II
Amit Ashok; Edward D. Franco; Michael E. Gehm; Mark A. Neifeld, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?