Unique opportunities to sample parameter space using physics-based synthetic x-ray data

Joel A. Greenberg; Daniel Pike; David Coccarelli

doi:10.1117/12.2664252

14 June 2023 Unique opportunities to sample parameter space using physics-based synthetic x-ray data

Joel A. Greenberg, Daniel Pike, David Coccarelli

Proceedings Volume 12531, Anomaly Detection and Imaging with X-Rays (ADIX) VIII; 1253105 (2023) https://doi.org/10.1117/12.2664252
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Physics-based synthetic data generation has been shown to complement empirical data in the rapid development of robust algorithms as well as their testing and interpretation. Quadridox’s QSim RT framework can generate rapidly large volumes of realistic X-ray data and associated metadata; while this data can be made to match traditional empirical data collections, the true value of physics-based synthetic data resides in the ways that it goes beyond empirical data to fully explore and map out the parameter space in which the data resides.

Conference Presentation

Citation Download Citation

Joel A. Greenberg, Daniel Pike, and David Coccarelli "Unique opportunities to sample parameter space using physics-based synthetic x-ray data", Proc. SPIE 12531, Anomaly Detection and Imaging with X-Rays (ADIX) VIII, 1253105 (14 June 2023); https://doi.org/10.1117/12.2664252

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