Noise reduction in elastograms using temporal stretching with multicompression averaging

Abstract

Elastography uses estimates of the time delay (obtained by cross-correlation) to compute strain estimates in tissue due to quasistatic compression. Because the time delay estimates do not generally occur at the sampling intervals, the location of the cross-correlation peak does not give and accurate estimate of the time delay. Sampling errors in the time-delay estimate are reduced using signal interpolation techniques to obtain subsample time-delay estimates. Distortions of the echo signals due to tissue compression introduce correlation artifacts in the elastogram. These artifacts are reduced by a combination of small compressions and temporal stretching of the postcompression signal. Random noise effects in the resulting elastograms are reduced by averaging several elastograms, obtained from successive small compressions (assuming that the errors are uncorrelated). Multicompression averaging with temporal stretching is shown to increase the signal-to-noise ratio in the elastogram by an order of magnitude, without sacrificing sensitivity, resolution or dynamic range. The strain filter concept is extended in this article to theoretically characterize the performance of multicompression averaging with temporal stretching.