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Synthetic dataset for visco-acoustic imaging.

Florian Faucher1,2, Otmar Scherzer1,3,4

  • 1Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, A-1090 Vienna, Austria.

Data in Brief
|May 22, 2023
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Summary
This summary is machine-generated.

This study introduces a computational dataset for ultrasonic wave propagation in human breast tissue, aiding ultrasound imaging research. The data helps evaluate reconstruction methods and inverse schemes under varying tissue properties and boundary conditions.

Keywords:
Full waveform inversionInverse problemsTime-harmonic wave propagationVisco-acoustic models

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Computational Science

Background:

  • Ultrasound imaging is crucial for medical diagnostics.
  • Accurate modeling of wave propagation in biological tissues is essential for image quality.
  • Tissue viscosity and boundary conditions significantly affect ultrasound wave behavior.

Purpose of the Study:

  • To generate a comprehensive computational dataset for simulating ultrasonic wave propagation in human breast tissue.
  • To provide data for evaluating ultrasound imaging reconstruction methods under attenuation uncertainty.
  • To assess the robustness of inverse schemes with complex boundary conditions.

Main Methods:

  • Simulated ultrasonic wave propagation in 2D and 3D domains using seven viscous models.
  • Incorporated physical parameters of a human breast with a high-contrast inclusion.
  • Modeled different boundary conditions (absorbing and reflecting) and acquisition setups.

Main Results:

  • Generated a dataset including physical parameters, acquisition setup, and pressure-wave data.
  • Simulations covered various viscous models and boundary conditions relevant to ultrasound imaging.
  • The dataset facilitates performance evaluation of reconstruction and inverse methods.

Conclusions:

  • The dataset serves as a valuable resource for advancing ultrasound imaging techniques.
  • It enables rigorous testing of methods dealing with attenuation uncertainty and multiple reflections.
  • Facilitates research into more robust and accurate ultrasound diagnostic tools.