Monte Carlo Framework for Physics-Based Design and Optimization of X-Ray Compressive Ghost Imaging Systems
Abstract
X-ray ghost imaging has emerged as a promising computational imaging modality capable of forming images from spatially integrated measurements. Unlike optical implementations, image formation is governed by multiple energy-dependent photon-matter interactions: photoelectric absorption, Compton scattering, and fluorescence. The relative contributions of these interactions depend on the source spectrum, sample geometry and composition, and detector configuration. We present a FLUKA-based Monte Carlo framework that models photon transport and predicts bucket signals generated by binary illumination patterns. The framework couples a physical scaling analysis, which converts the simulated bucket signals into photon numbers, tube loading and absorbed dose, with a ghost imaging reconstruction analysis of image quality and convergence. Our framework helps assess whether a given configuration is limited by the source output, the mask modulation or the reconstruction before any measurement is made. We evaluate the reconstruction for a centimeter-scale imaging system for an iron crown using one transmission detector and three off-axis scattering detectors over a range of source spectra. The results reveal how source characteristics and detector geometry influence reconstruction quality and radiation dose, providing quantitative guidelines for future X-ray ghost imaging system design. More broadly, this work establishes a predictive design framework for application-specific X-ray ghost imaging systems.
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BibTeX
@misc{shukrun2026monte,
title = {{Monte Carlo Framework for Physics-Based Design and Optimization of X-Ray Compressive Ghost Imaging Systems}},
author = {R. H. Shukrun and A. Ben-Yehuda and Y. Korotinsky and Y. Klein and O. Sefi and Y. Fried and L. Epstein and S. Shwartz},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.21334},
eprint = {2610.21334},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.21334},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Monte Carlo Framework for Physics-Based Design and Optimization of X-Ray Compressive Ghost Imaging Systems
AU - R. H. Shukrun
AU - A. Ben-Yehuda
AU - Y. Korotinsky
AU - Y. Klein
AU - O. Sefi
AU - Y. Fried
AU - L. Epstein
AU - S. Shwartz
PY - 2026
DA - 2026/10/15
PB - arXiv
DO - 10.48550/arxiv.2610.21334
UR - https://arxiv.org/abs/2610.21334
AB - X-ray ghost imaging has emerged as a promising computational imaging modality capable of forming images from spatially integrated measurements. Unlike optical implementations, image formation is governed by multiple energy-dependent photon-matter interactions: photoelectric absorption, Compton scattering, and fluorescence. The relative contributions of these interactions depend on the source spectrum, sample geometry and composition, and detector configuration. We present a FLUKA-based Monte Carlo framework that models photon transport and predicts bucket signals generated by binary illumination patterns. The framework couples a physical scaling analysis, which converts the simulated bucket signals into photon numbers, tube loading and absorbed dose, with a ghost imaging reconstruction analysis of image quality and convergence. Our framework helps assess whether a given configuration is limited by the source output, the mask modulation or the reconstruction before any measurement is made. We evaluate the reconstruction for a centimeter-scale imaging system for an iron crown using one transmission detector and three off-axis scattering detectors over a range of source spectra. The results reveal how source characteristics and detector geometry influence reconstruction quality and radiation dose, providing quantitative guidelines for future X-ray ghost imaging system design. More broadly, this work establishes a predictive design framework for application-specific X-ray ghost imaging systems.
ER -