Beamforming Approaches for Ultrafast Nonlinear Ultrasound Imaging

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Lai, Ting-Yu

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Recent advances in ultrafast contrast imaging have facilitated innovations such as super-resolutionimaging and ultrafast contrast-enhanced Doppler imaging (Chapter 1). It has become evident that combining ultrafast imaging with tissue harmonic imaging (THI) may offer improvements in image quality in clinical areas such as 4D THI and harmonic color flow (Chapter 1). In the first half of this work, we investigated the feasibility of combining ultrafast imaging with THI. We began with developing a numerical solution based on the Khokhlov-Zabolotskaya-Kuznetsov (KZK) to model the nonlinear propagation of sound beams produced by diagnostic arrays in tissue (Chapter 2). We then expanded our research for ultrafast THI and investigated the harmonic generation of a matrix array for identifying optimal beamforming strategies for 4D cardiac THI (Chapter 3). In the second half of this work, we proposed imaging approaches for improving tissue signal suppression and contrast sensitivity for ultrafast contrast imaging. We began with investigating the linear signal cancellation (tissue signal suppression) performance of the Verasonics research ultrasound scanner and compared it with the Philips iU22 (Chapter 4). We then studied the phase response of the microbubbles and tissue, and presented evidence that unique microbubble nonlinear dynamics can produce a phase response that can be used as a segmentation tool to further improve tissue signal suppression in contrast imaging (Chapter 5). Finally, we identified an aperture pattern for AM that improves the tissue signal suppression compared to the conventional AM. We also demonstrated that the additional phase response induced by the spatial difference between complementary half amplitude fields in OAM pulse sequences is useful for improving phase segmentation and image contrast (Chapter 6). We concluded with a summary of all the results and accomplishments and future directions of this work (Chapter 7).

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Thesis (Ph.D.)--University of Washington, 2021

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