Browsing by Subject "Elastography"
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Item Comparison of the Performance of Different Time Delay Estimation Techniques for Ultrasound Elastography(2011-10-21) Sambasubramanian, SrinathElastography 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.Item Effect of Temporal Acquisition Parameters on the Image Quality of Ultrasound Axial Strain Time-constant Elastograms(2011-08-02) Varghese, JoshuaRecent developments in ultrasound elastography have suggested the possibility of using elastographic methods to estimate the temporal mechanical properties of complex tissues. In this context, elastographic methods to image the axial strain time constant (TC) have been developed. The axial strain TC is a parameter that is related to the viscoelastic and poroelastic behavior of tissues. Estimation of this parameter can be done using curve fitting methods. However, the effect of temporal ultrasonic acquisition parameters, such as window of observation, acquisition rate, and input noise, on the image quality of the resultant TC elastograms has not been investigated yet. Elucidating such effects could be useful for diagnostic applications. This work explores the effects of varying windows of observation, acquisition rate, and input noise on the image quality (accuracy and signal-to-noise ratio (SNR)) of axial strain TC estimates and elastograms using a previously developed simulation model. By varying the amount of data collected as a percentage of the expected TC, the algorithms were able to compute a minimum threshold collection time for an accurate TC estimation as a percentage of the expected TC. The effect of acquisition parameters such as acquisition rate and input noise on the minimum threshold collection time was assessed. Experimental data, collected for previous experiments, were used as a proof of principle to corroborate the simulation findings. The results of this work suggest that there is a linear dependence of the total acquisition time necessary for accurate TC estimates on the true time constant value. The simulation results also indicate that it might be possible to make accurate estimates of the axial strain TC using small windows of observation (as small as 20% of the expected TC) with fast acquisition rates and high input SNR levels. Experimental results suggest that, in practice, a larger window of observation should be used to account for multiple noise sources typically not considered in simulations. This work also suggests that the minimum window of observation necessary for an accurate TC estimate is highly dependent on the acquisition frame rate and the input SNR level. Therefore, use of imaging systems with fast acquisition rates is recommended for studies aiming at measuring time-dependent phenomena in tissues.Item Statistical Analysis of a Three-dimensional Axial Strain and Axial-shear Strain Elastography Algorithm(2012-10-19) Li, MohanPathological phenomena often change the mechanical properties of the tissue. Therefore, estimation of tissue mechanical properties can be of clinical importance. Ultrasound elastography is a well-established strain estimation technique. Until recently, mainly 1D elastography algorithms have been developed. A few 2D algorithms have also been developed in the past. Both of these two types of technique ignore the tissue motion in the elevational direction, which could be a significant source of decorrelation in the RF data. In this thesis, a 3D elastography algorithm that estimates all the three components of tissue displacement is implemented and tested statistically. In this research, displacement fields of mechanical models are simulated. RF signals are then generated based on these displacement fields and used as the input of elastography algorithms. To evaluate the image quality of elastograms, absolute error, SNRe, CNRe and CNRasse are computed. The SNRe, CNRe and CNRasse values are investigated not only under different strain conditions, but also in different frame locations, which forms 3D strain filters. A statistical comparison between image qualities of the 3D technique and 2D technique is also provided. The results of this study show that the 3D elastography algorithm outperforms the 2D elastography algorithm in terms of image quality and robustness, especially under high strain conditions. This is because that the 3D algorithm estimates the elevational displacement, while the 2D technique only estimates the axial and lateral deformation. Since the elevational displacement could be an important source for the decorrelation in the RF data, the 3D technique is more effective and robust compared with the 2D technique.