Adaptive x-ray threat detection using sequential hypotheses testing with fan-beam experimental data (Conference Presentation)

Ratchaneekorn Thamvichai; Liang-Chih Huang; Amit Ashok; Qian Gong; David Coccarelli; Joel A. Greenberg; Michael E. Gehm; Mark A. Neifeld

doi:10.1117/12.2266756

7 June 2017 Adaptive x-ray threat detection using sequential hypotheses testing with fan-beam experimental data (Conference Presentation)

Ratchaneekorn Thamvichai, Liang-Chih Huang, Amit Ashok, Qian Gong, David Coccarelli, Joel A. Greenberg, Michael E. Gehm, Mark A. Neifeld

Author Affiliations +

Proceedings Volume 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II; 101870A (2017) https://doi.org/10.1117/12.2266756
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

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.

Conference Presentation

Citation Download Citation

Ratchaneekorn Thamvichai, Liang-Chih Huang, Amit Ashok, Qian Gong, David Coccarelli, Joel A. Greenberg, Michael E. Gehm, and Mark A. Neifeld "Adaptive x-ray threat detection using sequential hypotheses testing with fan-beam experimental data (Conference Presentation)", Proc. SPIE 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II, 101870A (7 June 2017); https://doi.org/10.1117/12.2266756

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