@article{01JT38HPZ2YXRMCKADWMJ3Z5YC,
  abstract     = {{Time-resolved high-resolution X-ray Computed Tomography (4D μCT) 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 constructing a sequence of 3D images from radiographic projections, recorded during time-frames that represent global sample states. This frame-based approach
limits the temporal resolution compared to dynamic radiography experiments, and it leads to an inflation of the amount of data. This results in 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 μCT reconstruction technique, named DYRECT, estimates individual attenuation evolution profiles for each position in the sample with time resolution down to the single projection level. This leads to a novel memory-efficient event-based representation for samples that display sudden, irreversible transitions over time. As little as three image volumes suffice for a broad range of applications: the initial attenuations, the final attenuations and the local transition times. This third volume represents spatially distributed 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 μCT time-frames.}},
  author       = {{Goethals, Wannes and Bultreys, Tom and Berg, Steffen and Boone, Matthieu and Aelterman, Jan}},
  editor       = {{McCann, Michael}},
  issn         = {{2573-0436}},
  journal      = {{IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING}},
  keywords     = {{Computed tomography,discrete event detection,fluid flow measurement,image representation,metal foam,reconstruction algorithms,Image reconstruction,Attenuation,Imaging,Iterative methods,Event detection,Dynamics,X-ray imaging,Three-dimensional displays,Spatial resolution,PORE-SCALE,CT,IMPROVEMENT,REDUCTION,MODEL}},
  language     = {{eng}},
  pages        = {{638--649}},
  title        = {{DYRECT computed tomography : DYnamic Reconstruction of Events on a Continuous Timescale}},
  url          = {{http://doi.org/10.1109/TCI.2025.3566241}},
  volume       = {{11}},
  year         = {{2025}},
}

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