| dc.description.abstract | Localized Harmonic Motion (LHM) Imaging is a new technique of ultrasound imaging which uses the localized stimulus of the oscillatory ultrasonic radiation force as produced by a modulated signal, and estimates the resulting harmonic displacement in the tissue in order to assess its underlying mechanical properties. This method can be highly localized and is considered as a non-invasive modality. In this thesis we first present the background information for LHM imaging and we compare this technique to other tissue mechanical properties imaging techniques. We then describe a setup for LHM induction and how the data is acquired and processed. We first focus on the transducer configuration, its characteristics and the housing built to combine the transducers, then the alignment of these transducers so they are confocal and can induce and detect motion in tissues, and finally we describe the local harmonic motion experiment setup including a supporting system and the induction/detection module. One of the most critical stages is the acquisition of the signal, since signals acquired by the imaging transducer always contain different sources of noise such as acoustic (standing waves, reflection from the tank, mechanical cross-talk between the transducers) and electric noise (electric cross-talk, noise of the high power amplifier) that we need to filter. Electronic filters were designed and implemented into our LHM experiment system. Additionally, digital filters were designed to further improve the performance of the system. We applied several kinds of digital notch filters (finite impulse response (FIR) and infinite impulse response (IIR) classes) and conduct analysis on the performance when obtaining LHM displacement information. After finishing the filtering and the setup, we performed LHM displacement experiments. We analyzed the obtained displacements as well as the noise observed in the final displacement waveforms, and the influence of analog and digital filters on the displacement detection. We finally measured the displacements induced by LHM on samples with different Young modulus and were able to differentiate them by the amplitude of the motion. Finally, we performed optimizations on the algorithm for LHM displacement calculations. Due to the large amount (462) of RF signals, it will typically take around 1h for a 41x41 points image. It was found that the digital filter was the most time consuming part of the processing and it was parallelized using graphics processing unit (GPU). | en_US |
