Window-Based Strain Estimation Using Weighted Displacement Obtained From Normalized Cross-Correlation

The common process of window-based ultrasound elastography (USE) is based on estimating the displacement fields and calculating the strain images by differentiating them. The displacement fields can be obtained using operators such as normalized cross-correlation (NCC). However, the provided displacements suffer from the artifacts caused by two dominant sources, the decorrelation, and amplitude modulation (AM) error. The main contribution of this study is to obtain strain images of higher quality and reduce the effect of artifacts. To this end, a weighted displacement estimation method is proposed. The proposed method consists of two steps. Some changes are applied to the windowing process, speeding up displacement estimation using the NCC method and filtering the provided displacements in two stages using median and weighted windows. We have assessed the performance of different weighted windows in conjunction with NCC on simulation and phantom data. This evaluation has not been implemented on the displacement fields yet. Thus, we tried to represent their improving effects on the estimated strains compared to the simple NCC approach and suggest the best window. The quantitative evaluation is performed in terms of elastographic signal to noise ratio (SNRe) and elastographic contrast to noise ratio (CNRe) on simulation and phantom data. The root mean square error (RMSE) comparison is also implemented for the simulation data. The visual and quantitative comparisons reveal that the proposed method substantially reduces artifacts, improves the strain image quality, and outperforms the NCC method.