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Direct Iterative Reconstruction of Computed Tomography Trajectories Reconstruction from limited number of projections with DIRECTT.

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Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens
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Fully experiment-based evaluation of few digital volume correlation techniques.

Bartosz Powierza1, Christian Gollwitzer1, Dagmar Wolgast2

  • 1Bundesanstalt für Materialforschung und -Prüfung (BAM), Unter den Eichen 87, 12205 Berlin, Germany.

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Digital Volume Correlation (DVC) techniques assess 3D image shifts for geometric analysis. This study introduces realistic methods to evaluate DVC accuracy across various materials.

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Area of Science:

  • * Materials Science and Engineering
  • * Computational Mechanics
  • * Image Analysis

Background:

  • * Digital Volume Correlation (DVC) is crucial for analyzing 3D image data from tomographic experiments.
  • * DVC quantifies local shifts, enabling geometric change analysis and image correction.
  • * Existing accuracy assessments often rely on synthetic or unrealistic data.

Purpose of the Study:

  • * To develop and apply realistic methods for evaluating Digital Volume Correlation (DVC) accuracy.
  • * To assess the performance of various DVC software packages.
  • * To investigate DVC accuracy on diverse material types.

Main Methods:

  • * Development of two novel, simple methods for DVC accuracy evaluation.
  • * Application of these methods to multiple DVC software programs.
  • * Testing on three distinct materials: tuff, sandstone, and concrete, with varying properties.

Main Results:

  • * Evaluation of DVC accuracy using realistic datasets and experimental setups.
  • * Comparison of DVC program performance across different material contrasts and structures.
  • * Identification of factors influencing DVC accuracy in practical applications.

Conclusions:

  • * The proposed methods provide a more realistic assessment of DVC accuracy.
  • * Results offer insights into the reliability of DVC techniques for material analysis.
  • * Findings aid in selecting appropriate DVC tools for specific research needs.