Rapid GPU-based simulation of x-ray transmission, scatter, and phase measurements for threat detection systems

Qian Gong; David Coccarelli; Razvan-Ionut Stoian; Joel Greenberg; Esteban Vera; Michael Gehm

doi:10.1117/12.2223244

12 May 2016 Rapid GPU-based simulation of x-ray transmission, scatter, and phase measurements for threat detection systems

Qian Gong, David Coccarelli, Razvan-Ionut Stoian, Joel Greenberg, Esteban Vera, Michael Gehm

Author Affiliations +

Proceedings Volume 9847, Anomaly Detection and Imaging with X-Rays (ADIX); 98470Q (2016) https://doi.org/10.1117/12.2223244
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

To support the statistical analysis of x-ray threat detection, we developed a very high-throughput x-ray modeling framework based upon GPU technologies and have created three different versions focusing on transmission, scatter, and phase. The simulation of transmission imaging is based on a deterministic photo-absorption approach. This initial transmission approach is then extended to include scatter effects that are computed via the Born approximation. For phase, we modify the transmission framework to propagate complex ray amplitudes rather than radiometric quantities. The highly-optimized NVIDIA OptiX API is used to implement the required ray-tracing in all frameworks, greatly speeding up code execution. In addition, we address volumetric modeling of objects via a hierarchical representation structure of triangle-mesh-based surface descriptions. We show that the x-ray transmission and phase images of complex 3D models can be simulated within seconds on a desktop computer, while scatter images take approximately 30-60 minutes as a result of the significantly greater computational complexity.

Citation Download Citation

Qian Gong, David Coccarelli, Razvan-Ionut Stoian, Joel Greenberg, Esteban Vera, and Michael Gehm "Rapid GPU-based simulation of x-ray transmission, scatter, and phase measurements for threat detection systems", Proc. SPIE 9847, Anomaly Detection and Imaging with X-Rays (ADIX), 98470Q (12 May 2016); https://doi.org/10.1117/12.2223244

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