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Determining 3D Flow Fields via Multi-camera Light Field Imaging
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A Continuity Flow Based Tomographic Reconstruction Algorithm for 4D Multi-Beam High Temporal-Low Angular Sampling.

Axel Henningsson1, Stephen A Hall1

  • 1Division of Solid Mechanics, Lund University, Ole Römers väg 1, 221 00 Lund, Sweden.

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|November 25, 2021
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Summary
This summary is machine-generated.

This study presents a new algorithm for 4D X-ray tomography, reconstructing spatiotemporal attenuation fields from limited angle data. The method effectively tracks dynamic granular systems, showing few angles can suffice for temporal evolution characterization.

Keywords:
4Dcontinuity equationsdynamictemporaltomography

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Area of Science:

  • Physics
  • Engineering
  • Computer Science

Background:

  • Dynamic systems require advanced imaging techniques for spatiotemporal analysis.
  • X-ray tomography typically demands extensive angular data, limiting its application in dynamic scenarios.

Purpose of the Study:

  • To develop a mathematical framework and numerical algorithm for 4D reconstruction of spatiotemporal attenuation fields.
  • To adapt X-ray tomography for rotation-free dynamic measurements with sparse angular and rich temporal information.

Main Methods:

  • Utilized the continuity equation for 4D reconstruction from multi-angle transmission measurements.
  • Employed a Finite Volumes method with a total variation diminishing monotonic upstream-centered scheme (TVDMUSCL) for propagating density volumes in time.
  • Validated the algorithm using discrete element-modeled granular system phantoms and an analytical ray projection model.

Main Results:

  • Demonstrated that reconstructions are feasible even with sparse angular data (more than 10 angles).
  • Showcased the algorithm's ability to approximate system kinematics through an artificial velocity field.
  • Highlighted the significant impact of temporal interpolation schemes on reconstruction accuracy.

Conclusions:

  • The developed algorithm enables 4D attenuation field reconstruction from limited-angle dynamic X-ray tomography data.
  • The approach is suitable for characterizing the temporal evolution of dynamic granular systems.
  • Careful selection of temporal interpolation is crucial for minimizing errors in reconstructed attenuation fields.