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Related Experiment Videos

Characterization of echographic image texture by cooccurrence matrix parameters

F M Valckx1, J M Thijssen

  • 1Clinical Physics Laboratory, University Hospital, Nijmegen, The Netherlands.

Ultrasound in Medicine & Biology
|January 1, 1997
PubMed
Summary

Cooccurrence matrix analysis effectively characterizes echographic image texture. Optimal parameters like entropy and angular second moment differentiate textures, while contrast and correlation detect structural periodicity.

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Area of Science:

  • Medical Imaging
  • Image Texture Analysis
  • Ultrasound Technology

Background:

  • Echographic image texture analysis is crucial for medical diagnosis.
  • Cooccurrence matrix analysis offers potential for quantitative texture characterization.
  • Understanding texture parameters aids in differentiating tissue types and pathologies.

Purpose of the Study:

  • To investigate the potential of cooccurrence matrix analysis for echographic image texture characterization.
  • To determine optimal parameters for differentiating textures and detecting structural periodicity in ultrasound images.
  • To evaluate the influence of various cooccurrence matrix parameters on texture analysis.

Main Methods:

  • Generated 1D echographic simulation data with varying scatterer densities and structural strengths.

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  • Estimated cooccurrence matrix parameters: angular second moment, contrast, correlation, entropy, and kappa.
  • Tuned analysis parameters including spatial displacement, gray levels, and window size.
  • Utilized Mahalanobis distance to differentiate textures and analyzed parameter correlations.

    • Main Results:

    • Cooccurrence matrix parameters saturated at 3-5 scatterers/resolution cell and 4-20 samples displacement.
    • An inverse relationship was found between window size and gray levels for texture differentiation.
    • Entropy and angular second moment were optimal for structureless textures (90 speckle cells, 64 gray levels).
    • Contrast and correlation were optimal for detecting periodicity in resolved structures.

    Conclusions:

    • Cooccurrence matrix analysis is a viable method for echographic texture characterization.
    • Specific parameters are optimal for differentiating texture types and identifying structural features.
    • The study provides guidance on parameter selection for enhanced ultrasound image analysis.