Direct volumetric reconstruction for highly compressive x-ray fluorescence ghost tomography

TL;DR

This paper introduces a direct volumetric XRF ghost tomography method that uses compressive structured illumination and multiplexed detection to significantly reduce measurement requirements while maintaining high spatial resolution.

Contribution

It presents a novel inverse problem approach that reconstructs 3D elemental distributions from all angles simultaneously, enabling scalable, efficient tomography of large samples.

Findings

Achieved 43X reduction in measurements compared to raster scanning.

Reconstructed 2.8 million voxel volume from only 400 measurements per angle.

Maintained spatial resolution and contrast despite reduced measurements.

Abstract

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 three-dimensional 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 43X 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.