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Eigenspace-based minimum variance beamformer combined with sign coherence factor: Application to linear-array

Sadaf Shamekhi1, Vijitha Periyasamy2, Manojit Pramanik2

  • 1Department of Biomedical Engineering, Tarbiat Modares University, Tehran, Iran.

Ultrasonics
|June 6, 2020
PubMed
Summary

This study introduces a novel Eigen-space based minimum variance (EIBMV) combined with sign coherence factor (SCF) method to significantly reduce noise in photoacoustic (PA) imaging. The proposed technique enhances image quality and signal-to-noise ratio (SNR) at greater depths.

Keywords:
Adaptive beamformingContrast enhancementImage reconstructionNoise reductionPhotoacoustic imaging

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Area of Science:

  • Biomedical Imaging
  • Optical Imaging
  • Ultrasound Imaging

Background:

  • Photoacoustic (PA) imaging offers high resolution and contrast but faces challenges with clutter noise and reduced signal-to-noise ratio (SNR) at depth.
  • Coherence factor (CF) weighting methods are used to mitigate noise and improve image quality in PA imaging.

Purpose of the Study:

  • To evaluate the effectiveness of combining an Eigen-space based minimum variance (EIBMV) beamformer with the sign coherence factor (SCF) for noise reduction in PA imaging.
  • To compare the proposed EIBMV-SCF method against traditional delay-and-sum (DAS) and minimum variance (MV) beamformers.

Main Methods:

  • Developed and implemented a hybrid beamforming approach integrating EIBMV and SCF.
  • Conducted comparative analyses using simulated data and both ex vivo and in vivo experimental data.
  • Assessed performance based on signal-to-noise ratio (SNR) improvements.

Main Results:

  • The EIBMV-SCF method demonstrated substantial SNR improvements: 94 dB (vs. DAS), 87.65 dB (vs. MV), and 62.29 dB (vs. EIBMV) in simulations.
  • Ex vivo and in vivo experiments showed significant SNR gains: 79.37/34.43 dB (vs. DAS), 77.25/26.96 dB (vs. MV), and 33.19/25.56 dB (vs. EIBMV).

Conclusions:

  • The combined EIBMV-SCF method effectively reduces noise and enhances SNR in photoacoustic imaging.
  • This approach offers a significant advancement for improving image quality, particularly at greater depths, compared to existing beamforming techniques.