Ultrasound Imaging Based on Cross-Correlation Mapping

In recent medical diagnosis, ultrasound strain imaging or elastography has been established as a useful technique to determine cancerous or abnormal tissues because a malignant tissue is stiffer than benign or normal tissue. In elastography, the gradient of tissue displacement is measured which is basically gives us the tissue strain and the calculated time delays between the pre- and post-compression gives us the displacement between tissues. This paper covers an imaging technique subjected to signal correlation. Signal correlation is a process which calculates the similarity between two signals as a function of displacement of one respect to another signal. We developed 2D finite element tissue mimicking phantom models based on real tissue properties using ANSYS software having a tumor inclusion surrounded by soft tissue. We have simulated the synthetic tissue for different inclusion tissue properties for a given displacement. From the ANSYS simulation model, the pre- and post-compression data were exported. Then, to acquire the ultrasound pre- and post-compression RF signals an ultrasound simulation was done using FIELD II for a more realistic simulation. 2D cross correlation MATLAB function was used to estimate the time delay between pre- and post-compression RF signals. Using MATLAB surf tool, the estimated correlation coefficient was mapped. The map shows a promising result to distinguish between a normal and abnormal tissue.