Two-dimensional autocorrelation method for ultrasound-based strain estimation

Ultrasound strain imaging maps the tissue stiffness in the region of interest by estimating strain when the tissue is stressed. Pre-stress and post-stress ultrasound echoes are processed to estimate the displacements, and the strain image is computed by a spatial derivative of the estimated displacement. Due to the nature of derivative operations, smaller errors in displacement estimation can cause large noise in the computed strain image. When tissue displacements are estimated using the phase of the autocorrelation between the pre-stress and post-stress data (i.e., 1D autocorrelation method), it has been previously reported that local variations in ultrasonic center frequency due to speckle can introduce errors in the estimated displacement. We have developed a new method to compute strain based on two-dimensional autocorrelation. By estimating the local ultrasound frequency, we can improve the accuracy of displacement estimates and hence reduce the noise in strain images. We have analyzed the effect of local frequency changes on noise in strain images and the improvement in the strain signal-to-noise ratio with the 2D autocorrelation method. The simulation results are supported by experiments with homogenous gelatin phantoms and show that strain signal-to-noise ratio with 2D autocorrelation is consistently higher than that with ID autocorrelation. The 2D autocorrelation can increase the strain signal-to-noise ratio by up to 200%, which leads us to believe that our estimation method can significantly improve the quality of strain images.