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Tissue Strain Estimation Using a Lagrangian Speckle Model

  • R. L. Maurice
  • M. Bertrand
Part of the Acoustical Imaging book series (ACIM, volume 23)

Abstract

Accurate assessment of tissue motion from spatio-temporal changes in ultrasound speckles is a key factor in computing high signal-to-noise ratio (SNR) elastograms or correlation-based flow profiles. Provided the tissue (or fluid) is subjected to a simple translation movement, reliable sub-wavelength displacement estimates can be obtained through cross-correlation delay computation. On the other hand when the tissue is subjected to more complex movement, displacement estimates are generally found to be less accurate; indeed the changes in speckle patterns that result from such a motion act as the noise source often responsible for most of the displacement estimate variance. In this paper we propose a method to estimate 2-D motion while optimally compensating for speckle decorrelation. The method is based on a Lagrangian speckle model we proposed in

Keywords

Point Spread Function Quantization Noise Inverse Filter Tissue Motion Displacement Estimate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • R. L. Maurice
    • 1
    • 2
  • M. Bertrand
    • 1
    • 2
  1. 1.Institut de génie biomédical, École PolytechniqueMontréalCanada
  2. 2.Institut de Cardiologie de MontréalMontréalCanada

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