X-ray ghost tomography: denoising, dose fractionation and mask considerations

TL;DR

This paper explores the adaptation of conventional tomography techniques to X-ray ghost imaging, addressing denoising, dose management, and mask considerations through numerical simulations for potential practical applications.

Contribution

It introduces the first comprehensive study of X-ray ghost tomography, adapting existing methods and analyzing key challenges like noise reduction and dose optimization.

Findings

Effective denoising schemes are identified.

Dose fractionation impacts are analyzed.

Mask ensemble considerations are discussed.

Abstract

Ghost imaging has recently been successfully achieved in the X-ray regime; due to the penetrating power of X-rays this immediately opens up the possibility of X-ray ghost tomography. No research into this topic currently exists in the literature. Here we present adaptations of conventional tomography techniques to this new ghost imaging scheme. Several numerical implementations for tomography through X-ray ghost imaging are considered. Specific attention is paid to schemes for denoising of the resulting tomographic reconstruction, issues related to dose fractionation, and considerations regarding the ensemble of illuminating masks used for ghost imaging. Each theme is explored through a series of numerical simulations, and several suggestions offered for practical realisations of X-ray ghost tomography.