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Frequency diversity speckle processing.

S M Gehlbach1, F G Sommer

  • 1Kesa Corporation, Santa Clara, CA 95054.

Ultrasonic Imaging
|April 1, 1987
PubMed
Summary
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Digital filtering of ultrasonic waveform data improved signal-to-target boundaries in phantom images. Both coherent and incoherent processing methods for speckle reduction proved equally effective.

Area of Science:

  • Medical Imaging
  • Ultrasound Technology
  • Digital Signal Processing

Background:

  • Ultrasound imaging is crucial for medical diagnostics.
  • Speckle noise degrades image quality and obscures details.
  • Effective speckle reduction is vital for accurate interpretation.

Purpose of the Study:

  • To evaluate digital filtering techniques for speckle reduction in ultrasound images.
  • To assess the impact of filtering on signal-to-target boundary definition.
  • To compare coherent and incoherent processing methods for image enhancement.

Main Methods:

  • Digitizing and processing ultrasonic waveform data from a tissue phantom.
  • Applying digital filters for speckle reduction to waveform data.

Related Experiment Videos

  • Performing coherent and incoherent image averaging on processed data.

    • Main Results:

    • Processed images exhibited enhanced signal-to-target boundaries compared to unprocessed images.
    • Digital filtering effectively reduced speckle noise.
    • Coherent and incoherent processing yielded equivalent results in this study.

    Conclusions:

    • Digital filtering of ultrasonic waveform data is an effective method for speckle reduction.
    • Enhanced boundary definition improves the clarity of ultrasonic images.
    • Both coherent and incoherent processing approaches are viable for ultrasound image enhancement.