Accelerated iterative tomographic reconstruction with x-ray edge illumination

TL;DR

This paper presents an improved iterative tomographic reconstruction method using x-ray edge illumination, achieving faster computation, higher resolution, and better contrast-to-noise ratio through experimental and algorithmic enhancements.

Contribution

The study introduces a sampling strategy for illumination curves that reduces model complexity and computational time, along with numerical improvements for faster, higher-quality reconstructions.

Findings

30% spatial resolution improvement over non-iterative methods

Order of magnitude speed increase in reconstruction process

Enhanced contrast-to-noise ratio in reconstructed images

Abstract

Compared to standard tomographic reconstruction, iterative approaches offer the possibility to account for extraneous experimental influences, which allows for a suppression of related artifacts. However, the inclusion of corresponding parameters in the iterative forward model typically leads to longer computation times. Here, we demonstrate experimentally for phase sensitive X-ray imaging based on the edge illumination principle that inadequately sampled illumination curves result in ring artifacts in tomographic reconstructions. We take advantage of appropriately sampled illumination curves instead, which enables us to eliminate the corresponding parameter from the forward model and substantially increase computational speed. In addition, we demonstrate a 30\% improvement in spatial resolution of the iterative approach compared with the standard non-iterative single shot approach. Further, we report on several significant improvements in our numerical implementation of the iterative approach, which we make available online with this publication. Finally, we show that the combination of both experimental and algorithmic advancement lead to a total speed increase by one order of magnitude and an improved contrast to noise ratio in the reconstructions.