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Updated: May 1, 2026

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Ultrasound elastography using empirical mode decomposition analysis.

Sajjad Sadeghi1, Hamid Behnam1, Jahan Tavakkoli2

  • 1Department of Medical Engineering, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Narmak, Iran.

Journal of Medical Signals and Sensors
|April 4, 2014
PubMed
Summary

Empirical Mode Decomposition (EMD) enhances ultrasound elastography by improving image quality. This method, using intrinsic mode functions (IMFs), boosts signal-to-noise and contrast-to-noise ratios in tissue and tumor imaging.

Keywords:
Elastogramelastographyempirical mode decompositionintrinsic mode function

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Area of Science:

  • Medical imaging
  • Biomedical engineering
  • Signal processing

Background:

  • Ultrasound elastography visualizes soft-tissue elasticity non-invasively.
  • Image formation involves estimating time delays from ultrasound radio frequency (RF) signals before and after compression.
  • Elastograms are derived from the first differentiation of displacement estimations.

Purpose of the Study:

  • To develop an elastogram using Empirical Mode Decomposition (EMD).
  • To evaluate the efficacy of EMD in improving elastogram quality.
  • To compare EMD's performance with conventional displacement estimation methods.

Main Methods:

  • Applied Empirical Mode Decomposition (EMD) to decompose RF signals into Intrinsic Mode Functions (IMFs).
  • Utilized two datasets: a normal/cooked tissue phantom and malignant breast tumor data.
  • Employed cross-correlation and wavelet transform for displacement estimation.
  • Assessed image quality using Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR).

Main Results:

  • EMD application improved image quality in both displacement estimation methods.
  • For the tissue phantom, EMD improved CNR and SNR by approximately 16 dB and 9 dB (cross-correlation), and 14 dB and 10 dB (wavelet transform).
  • For breast tumor data, EMD improved CNR and SNR by approximately 18 dB and 7 dB (cross-correlation), and 17 dB and 6 dB (wavelet transform).

Conclusions:

  • Empirical Mode Decomposition (EMD) effectively enhances ultrasound elastography.
  • The use of IMFs derived from EMD improves image quality metrics (SNR and CNR).
  • EMD offers a valuable processing technique for more accurate soft-tissue elasticity imaging.