False peak error removal using local difference median analysis in elastography

Outlier due to false peak error (FPE) usually emerges during displacement estimation of ultrasound elastography, for which the performance of the resulted elastogram is degraded evidently. In this paper, a new method to remove the displacement outliers is proposed. The method is carried out in two steps, i.e., outlier detection and replacement. For the first step, the median of local displacement difference is computed and compared with a threshold deduced according to the application parameters such as the maximum tissue strain, the signal-to-noise ratio of the displacement estimation (SNRe), and the dimensions of the local window. If the median is larger than the threshold, the displacement point is deemed an outlier. For the second step, the displacement outlier is replaced with the median of the displacement points in a local region. The results from the experiments with theoretical data contaminated by artificial outliers show that the proposed method is effective in removing the displacement outliers when the outlier points is not more than a reasonable ratio in all the displacement points. Meanwhile, the result of breast phantom experiment further verifies the validity of this method.