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

Autor: Kingston, Andrew M., Myers, Glenn R., Pelliccia, Daniele, Svalbe, Imants D., Paganin, David M.
Rok vydání: 2018
Předmět:
Zdroj: IEEE Transactions on Computational Imaging 5, 136-149 (2019)
Druh dokumentu: Working Paper
Popis: 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.
Databáze: arXiv