DYRECT Computed Tomography: DYnamic Reconstruction of Events on a Continuous Timescale

TL;DR

DYRECT is a novel 4D CT reconstruction method that estimates continuous event times and attenuation profiles, enabling high temporal resolution with less data and computational cost compared to traditional frame-based approaches.

Contribution

The paper introduces DYRECT, a memory-efficient event-based 4D μCT reconstruction technique that estimates continuous transition times using only three image volumes.

Findings

Effectively pinpoints transition times with less than a tenth of the projections needed for traditional methods.

Validated on synthetic and experimental data, demonstrating high temporal resolution.

Reduces data and computational costs compared to conventional frame-based 4D μCT.

Abstract

Time-resolved high-resolution X-ray Computed Tomography (4D $\mu$CT) is an imaging technique that offers insight into the evolution of dynamic processes inside materials that are opaque to visible light. Conventional tomographic reconstruction techniques are based on recording a sequence of 3D images that represent the sample state at different moments in time. This frame-based approach limits the temporal resolution compared to dynamic radiography experiments due to the time needed to make CT scans. Moreover, it leads to an inflation of the amount of data and thus to costly post-processing computations to quantify the dynamic behaviour from the sequence of time frames, hereby often ignoring the temporal correlations of the sample structure. Our proposed 4D $\mu$CT reconstruction technique, named DYRECT, estimates individual attenuation evolution profiles for each position in the sample. This leads to a novel memory-efficient event-based representation of the sample, using as little as three image volumes: its initial attenuation, its final attenuation and the transition times. This third volume represents local events on a continuous timescale instead of the discrete global time frames. We propose a method to iteratively reconstruct the transition times and the attenuation volumes. The dynamic reconstruction technique was validated on synthetic ground truth data and experimental data, and was found to effectively pinpoint the transition times in the synthetic dataset with a time resolution corresponding to less than a tenth of the amount of projections required to reconstruct traditional $\mu$CT time frames.