Determination of scan-plane motion using speckle decorrelation: Theoretical considerations and initial test

Jian Feng Chen, J. Brian Fowlkes*, Paul L. Carson, Jonathan M. Rubin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


The correlation function of the echo signal intensities at a fixed region on a series of B-mode images is directly related to the change of speckle patterns between these images. An indication is given here of how the rate of the change of that correlation function can be used to estimate the scan-plane motion in any direction relative to the imaged tissue or other material. In this first implementation it is assumed that the statistical properties of the echo signals follow those of a complex circular Gaussian, and the case is considered of diffusely scattering tissue with many fine particles per resolution cell and with no phase distortion. The method is applied to data from a one-dimensional linear array and initial results are presented for scanning a tissue-mimicking phantom in the elevational direction of the transducer. Experimental results are in good agreement with the predictions. The current method should provide a good indication of the local rate of scan-head motion in those tissues in which the normalized correlation function of the echo signal intensities behaves, or can be made to behave, as it would for a medium with uniform acoustic properties and containing many, randomly distributed, pointlike scatterers, although application might be made to other situations where a deterministic condition exists for the correlation between images taken at differing locations within a volume.

Original languageEnglish (US)
Pages (from-to)38-44
Number of pages7
JournalInternational Journal of Imaging Systems and Technology
Issue number1
StatePublished - 1997


  • 3D
  • Decorrelation
  • Motion estimation
  • Speckle
  • Ultrasound

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Software
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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