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X-ray fluorescence (XRF) enables element-specific, nondestructive imaging, but conventional raster scanning scales poorly with sample size, particularly for tomography, because measurements must be repeated at every projection angle and spatial position. We demonstrate direct volumetric XRF ghost tomography, which replaces point-by-point acquisition with compressive structured illumination and multiplexed fluorescence detection. Rather than reconstructing projections at each angle and then applying standard tomographic reconstruction, we recover the 3D elemental distribution by solving a single inverse problem that jointly incorporates measurements from all angles. For a volume of 2.8 million voxels, we reconstruct the elemental distribution from only 400 measurements per angle, achieving a 43× reduction relative to raster scanning while maintaining spatial resolution and contrast. By exploiting sparsity directly in the volumetric domain, this approach enables scalable, multi-element XRF tomography of large and heterogeneous samples under stringent acquisition time constraints.
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Yehuda et al. (2026) studied this question.
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