Methods for the estimation of the tissue motion using digitized ultrasound echo signals

Tissue motion estimation in ultrasound images plays a central role in many modern signal processing applications, including tissue characterization, strain and velocity imaging, and tissue viscoelasticity imaging. Therefore, the performance of tissue motion estimation is of significant importance. Also, its computational cost determines if it can be implemented in real-time so that it can be used clinically. This thesis presents several efficient methods for accurate estimation of tissue motion using digitized ultrasound echo signals. First, sample tracking algorithms are presented as a new class of motion estimators. These algorithms are based on the tracking of individual samples using a continuous representation of the reference echo signal. Simulations and experimental results on tissue mimicking phantoms show that sample tracking algorithms significantly outperform common algorithms in terms of accuracy, precision, sensitivity, and resolution. However, their performance degrades in the presence of noise. To improve the performance of motion estimation in multi-dimensions, pattern matching interpolation techniques are studied and new interpolation techniques are presented. Simulation and experimental results show that, with small computational overhead, the proposed interpolation techniques significantly improve the accuracy and the precision of motion estimation in both 2D and 3D. Employing these techniques, real-time 2D motion tracking software is developed. Furthermore, the performance of the proposed 2D estimators is compared with that of 2D tracking using angular compounding. The results show that the proposed interpolation methods bring the performance of pattern matching techniques close to that of 2D compound tracking. Finally, angular compounding is combined with custom pulse sequencing and delay cancellation techniques to develop a system that estimates the motion vectors at very high frame rates (> 500 Hz) in real-time. The application of the system in the study of the propagation of mechanical waves for tissue characterization is also presented.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat