Ultrasound in Medicine and Biology
Volume 33, Issue 1 , Pages 74-81, January 2007

Error analysis of ultrasonic tissue doppler velocity estimation techniques for quantification of velocity and strain

  • Michael J. Bennett

      Affiliations

    • School of Clinical Sciences and Community Health, Medical and Radiological Sciences, Medical Physics, The Chancellor’s Building, 49, Little France Crescent, Edinburgh. EH16 4SB UK
    • Corresponding Author InformationAddress correspondence to: Michael J. Bennett, School of Clinical Sciences and Community Health, Medical and Radiological Sciences, Medical Physics, The Chancellor’s Building, 49, Little France Crescent, Edinburgh. EH16 4SB UK.
  • ,
  • Steve McLaughlin

      Affiliations

    • School of Engineering and Electronics, The University of Edinburgh, The King’s Buildings, Mayfield Road, Edinburgh. EH9 3JL UK
  • ,
  • Tom Anderson

      Affiliations

    • School of Clinical Sciences and Community Health, Medical and Radiological Sciences, Medical Physics, The Chancellor’s Building, 49, Little France Crescent, Edinburgh. EH16 4SB UK
  • ,
  • W. Norman McDicken

      Affiliations

    • School of Clinical Sciences and Community Health, Medical and Radiological Sciences, Medical Physics, The Chancellor’s Building, 49, Little France Crescent, Edinburgh. EH16 4SB UK

Abstract 

Recent work in the field of Doppler tissue imaging has focused mainly on the quantification of results involving the use of techniques of strain and strain-rate imaging. These results are based on measuring a velocity gradient between two points, a known distance apart, in the region-of-interest. Although many recent publications have demonstrated the potential of this technique in clinical terms, the method still suffers from low repeatability. The work presented here demonstrates, through the use of a rotating phantom arrangement and a custom developed single element ultrasound system, that this is a consequence of the fundamental accuracy of the technique used to estimate the original velocities. Results are presented comparing the performance of the conventional Kasai autocorrelation velocity estimator with those obtained using time domain cross-correlation and the complex cross-correlation model based estimator. The results demonstrate that the complex cross-correlation model based technique is able to offer lower standard deviations of the velocity gradient estimations compared with the Kasai algorithm. (E-mail: mjb@ee.ed.ac.uk)

Key Words: Doppler tissue imaging, Strain imaging, Strain rate, Velocity estimation, Kasai autocorrelation, Complex cross correlation model

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PII: S0301-5629(06)01753-4

doi:10.1016/j.ultrasmedbio.2006.07.040

Ultrasound in Medicine and Biology
Volume 33, Issue 1 , Pages 74-81, January 2007