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Information-theoretic analysis of fixed Gantry x-ray computed tomography transmission system for threat detection (Conference Presentation)
Author(s): Jay Voris; Yijun Ding; Ratchaneekorn Thamvichai; Joel A. Greenberg; David Coccarelli; Michael E. Gehm; Eric Johnson; Carl Bosch; Amit Ashok
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Paper Abstract

Detecting material anomalies in baggage requires a high-throughput X-ray measurement system that can reliably inform the user/classifier of pertinent material characteristics. We have developed a comprehensive high-fidelity simulation framework capable of modeling a multi-energy X-ray fixed gantry computed tomography transmission system. Our end-to-end simulation framework includes experimentally validated models of sources and detectors, as well as virtual bags to emulate the X-ray measurements generated by the fixed gantry X-ray CT system. This simulation capability enables us to conduct exploratory system trade-off studies around the current fixed gantry system, in terms of the source detector geometry, detector energy resolution and other relevant system parameters to assess their impact on the threat detection performance. Using scalable information-theoretic metrics, evaluated on simulated system data, we are able to provide quantitative performance bounds on the performance of the candidate system designs. In this work, we will report results of our initial system design trade-off studies focused on detector energy resolution and energy partitioning and how they impact the threat detection performance.

Paper Details

Date Published: 14 May 2019
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Proc. SPIE 10999, Anomaly Detection and Imaging with X-Rays (ADIX) IV, 109990I (14 May 2019); doi: 10.1117/12.2519812
Show Author Affiliations
Jay Voris, College of Optical Sciences, The Univ. of Arizona (United States)
Yijun Ding, College of Optical Sciences, The Univ. of Arizona (United States)
Ratchaneekorn Thamvichai, The Univ. of Arizona (United States)
Joel A. Greenberg, Duke Univ. (United States)
David Coccarelli, Duke Univ. (United States)
Michael E. Gehm, Duke Univ. (United States)
Eric Johnson, SureScan Corp. (United States)
Carl Bosch, SureScan Corp. (United States)
Amit Ashok, College of Optical Sciences, Univ of Arizona (United States)


Published in SPIE Proceedings Vol. 10999:
Anomaly Detection and Imaging with X-Rays (ADIX) IV
Amit Ashok; Joel A. Greenberg; Michael E. Gehm, Editor(s)

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