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Cortical Bone Assessment Using Ultrasonic Guided Waves: A Reproducibility Study in a Healthy Population
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Full waveform inversion using frequency shift envelope-based global correlation norm for ultrasound computed

Yun Wu1, Weicheng Yan1, Zhaohui Liu1

  • 1Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China.

Physics in Medicine and Biology
|April 9, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new ultrasound computed tomography (USCT) method, frequency shift envelope-based global correlation norm (FSEGCN), to improve sound speed imaging. FSEGCN successfully reconstructs accurate images without low-frequency data, overcoming limitations of traditional full waveform inversion (FWI).

Keywords:
envelopefrequency shiftglobal correlation normultrasound computed tomography

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Acoustics

Background:

  • Ultrasound computed tomography (USCT) enables quantitative tissue sound speed measurement.
  • Full waveform inversion (FWI) reconstructs high-resolution sound speed images but is prone to cycle-skipping, leading to local minima.
  • Cycle-skipping, caused by phase differences exceeding half a cycle, is typically avoided using low-frequency data, which is often unavailable in practical imaging systems.

Purpose of the Study:

  • To develop a novel method for accurate sound speed imaging in USCT that circumvents the cycle-skipping problem without relying on low-frequency information.
  • To evaluate the performance of the proposed method against existing techniques like FWI, envelope inversion (EI), global correlation norm (GCN), and envelope-based global correlation norm (EGCN).

Main Methods:

  • Proposed a frequency shift envelope-based global correlation norm (FSEGCN) technique.
  • Utilized an artificial low-frequency source wavelet to generate synthetic data for inversion.
  • Compared FSEGCN with FWI, EI, GCN, and EGCN using a concentric circle phantom, human head, and calf phantoms, specifically in scenarios lacking original low-frequency information.

Main Results:

  • FSEGCN successfully reconstructed sound speed images close to the exact model without low-frequency information.
  • Traditional methods (FWI, EI, GCN, EGCN) failed to achieve accurate reconstructions in the absence of low-frequency data.
  • Application of artificial source wavelets in human head and calf phantoms reduced image artifacts and improved reconstruction robustness.

Conclusions:

  • FSEGCN offers a robust solution for accurate sound speed imaging in USCT, particularly when low-frequency data is unavailable.
  • The use of artificial source wavelets is a viable strategy to mitigate artifacts and enhance the reliability of USCT reconstructions.
  • This method advances quantitative ultrasound imaging by overcoming a critical limitation of conventional full waveform inversion.