An Information-Theoretic Analysis of X-Ray Architectures for Anomaly Detection

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X-ray scanning equipment currently establishes a first line of defense in the aviation security space. The efficacy of these scanners is crucial to preventing the harmful use of threatening objects and materials. In this dissertation, I introduce a principled approach to the analyses of these systems by exploring performance limits of system architectures and modalities. Moreover, I validate the use of simulation as a design tool with experimental data as well as extend the use of simulation to create high-fidelity realizations of a real-world system measurements.

Conventional performance analysis of detection systems confounds the effects of the system architecture (sources, detectors, system geometry, etc.) with the effects of the detection algorithm. We disentangle the performance of the system hardware and detection algorithm so as to focus on analyzing the performance of just the system hardware. To accomplish this, we introduce an information-theoretic approach to this problem. This approach is based on a metric derived from Cauchy-Schwarz mutual information and is analogous to the channel capacity concept from communications engineering. We develop and utilize a framework that can produce thousands of system simulations representative of a notional baggage ensembles. These simulations and the prior knowledge of the virtual baggage allow us to analyze the system as it relays information pertinent to a detection task.

In this dissertation, I discuss the application of this information-theoretic approach to study variations of X-ray transmission architectures as well as novel screening systems based on X-ray scatter and phase. The results show how effective use of this metric can impact design decisions for X-ray systems. Moreover, I introduce a database of experimentally acquired X-ray data both as a means to validate the simulation approach and to produce a database ripe for further reconstruction and classification investigations. Next, I show the implementation of improvements to the ensemble representation in the information-theoretic material model. Finally I extend the simulation tool toward high-fidelity representation of real-world deployed systems.





Coccarelli, David Scott (2018). An Information-Theoretic Analysis of X-Ray Architectures for Anomaly Detection. Dissertation, Duke University. Retrieved from


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