Bayesian optimization of laser-Compton x-ray sources for medical imaging applications

Trevor Reutershan; Haytham H. Effarah; C. P. J. Barty

doi:10.1117/12.2654377

7 April 2023 Bayesian optimization of laser-Compton x-ray sources for medical imaging applications

Trevor Reutershan, Haytham H. Effarah, C. P. J. Barty

Proceedings Volume 12463, Medical Imaging 2023: Physics of Medical Imaging; 124633V (2023) https://doi.org/10.1117/12.2654377
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Laser-Compton x-ray sources have many advantages over traditional x-ray tubes for use in medical imaging due to their monoenergetic energy spectrum, tunability, high-flux, and low-dose potential. These properties can specifically be taken advantage of in the context of K-edge subtraction (KES) imaging. Previous optimization approaches are time-consuming by scanning over high-dimensional parameter spaces. Here, we show how a Bayesian optimization routine optimizes LCS source parameters in only a fraction of the computational time. Using this approach, we found a configuration that produces non-inferior image quality in KES mammography compared to a previously optimized direct energy tuning technique. Moreover, a successfully optimized implementation of scanning K-edge subtraction imaging was realized applying this Bayesian approach.

Citation Download Citation

Trevor Reutershan, Haytham H. Effarah, and C. P. J. Barty "Bayesian optimization of laser-Compton x-ray sources for medical imaging applications", Proc. SPIE 12463, Medical Imaging 2023: Physics of Medical Imaging, 124633V (7 April 2023); https://doi.org/10.1117/12.2654377

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