Creating an experimental testbed for information-theoretic analysis of architectures for x-ray anomaly detection

David Coccarelli; Joel A. Greenberg; Sagar Mandava; Qian Gong; Liang-Chih Huang; Amit Ashok; Michael E. Gehm

doi:10.1117/12.2263033

1 May 2017 Creating an experimental testbed for information-theoretic analysis of architectures for x-ray anomaly detection

David Coccarelli, Joel A. Greenberg, Sagar Mandava, Qian Gong, Liang-Chih Huang, Amit Ashok, Michael E. Gehm

Author Affiliations +

Proceedings Volume 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II; 1018709 (2017) https://doi.org/10.1117/12.2263033
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

Anomaly detection requires a system that can reliably convert measurements of an object into knowledge about that object. Previously, we have shown that an information-theoretic approach to the design and analysis of such systems provides insight into system performance as it pertains to architectural variations in source fluence, view number/angle, spectral resolution, and spatial resolution.¹ However, this work was based on simulated measurements which, in turn, relied on assumptions made in our simulation models and virtual objects. In this work, we describe our experimental testbed capable of making transmission x-ray measurements. The spatial, spectral, and temporal resolution is sufficient to validate aspects of the simulation-based framework, including the forward models, bag packing techniques, and performance analysis. In our experimental CT system, designed baggage is placed on a rotation stage located between a tungsten-anode source and a spectroscopic detector array. The setup is able to measure a full 360° rotation with 18,000 views, each of which defines a 10 ms exposure of 1,536 detector elements, each with 64 spectral channels. Measurements were made of 1,000 bags that comprise 100 clutter instantiations each with 10 different target materials. Moreover, we develop a systematic way to generate bags representative of our desired clutter and target distributions. This gives the dataset a statistical significance valuable in future investigations.

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Citation Download Citation

David Coccarelli, Joel A. Greenberg, Sagar Mandava, Qian Gong, Liang-Chih Huang, Amit Ashok, and Michael E. Gehm "Creating an experimental testbed for information-theoretic analysis of architectures for x-ray anomaly detection", Proc. SPIE 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II, 1018709 (1 May 2017); https://doi.org/10.1117/12.2263033

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