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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.
Joel A. Greenberg,Daniel Pike, andDavid 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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Joel A. Greenberg, Daniel Pike, 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