Comparison of the Performance of Different Time Delay Estimation Techniques for Ultrasound Elastography
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Elastography is a non-invasive medical imaging modality that is used as a diagnostic tool for the early detection of several pathological changes in soft tissues. Elastography techniques provide the local strain distributions experienced by soft tissues due to compression. The resulting strain images are called ?elastograms?. In elastography, the local tissue strains are usually estimated as the gradient of local tissue displacement. The local tissue displacements are estimated from the time delays between gated pre- and post-compression echo signals. The quality of the resulting elastograms is highly dependent on the accuracy of these local displacement estimates. While several time delay estimation (TDE) techniques have been proposed for elastography applications, there is a lack of systematic study that statistically compares the performance of these techniques. This information could prove to be of great importance to improve currently employed elastographic clinical methods. This study investigates the performance of selected time delay estimators for elastography applications. Time delay estimators based on Generalized Cross Correlation (GCC), Sum of Squared Differences (SSD) and Sum of Absolute Differences (SAD) are proposed and implemented. Within the class of GCC algorithms, we further consider: an FFT-based cross correlation algorithm (GCC-FFT), a hybrid time-domain and frequency domain cross correlation algorithm with prior estimates (GCC-PE) and an algorithm based on the use of fractional Fourier transform to compute the cross correlation (GCC -FRFT) . Image quality factors of the elastograms obtained using the different TDE techniques are analyzed and the results are compared using standard statistical tools. The results of this research suggests that correlation based techniques outperform SSD and SAD techniques in terms of SNRe, CNRe, dynamic range and robustness. The sensitivity of GCC-FFT and SSD were statistically similar and statistically higher than those of all other methods. Within the class of GCC methods, there is no statistically significant difference between SNRe of GCC-FFT, GCC-PE and GCC ?FRFT for most of the strain values considered in this study. However, in terms of CNRe, GCC-FFT and GCC-FRFT were significantly better than other TDE algorithms. Based on these results, it is concluded that correlation-based algorithms are the most effective in obtaining high quality elastograms.