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A comparative evaluation of two Synthetic Transmit Aperture with Virtual Source beamforming methods in biomedical ultrasound

University of British Columbia

This thesis studies the Synthetic Transmit Aperture with Virtual Source (STA-VS) beamforming method, which is an emerging technique in biomedical ultrasound. It promises better imaging quality compared to conventional beamforming, with the same imaging speed. Several specific realizations of the STA-VS methods have been proposed in the literature and the topic is an active research area. The first part of the thesis examines two realizations of the STA-VS method, namely the Synthetic Aperture Sequential Beamforming (SASB) method and the bi-directional pixel-based focusing (BiPBF) method. Studies are performed with both ultrasound simulation software and a commercial ultrasound scanner's research interface. The studies show that the STA-VS methods can improve the spatial and contrast resolution of ultrasound imaging. The two stage implementation of SASB has lower complexity between the two STA-VS methods. However, compared to other beamformers, SASB is more susceptible to speed-of-sound (SOS) errors in the beamforming calculations. The second part of the thesis proposes an SOS estimation and correction algorithm. The SOS estimation part of the algorithm is based on second-order polynomial fitting to point scatterers in pre-beamformed data, and is specifically applicable to the two stage realization of the SASB method. The SOS correction part of the algorithm is incorporated into the second stage beamforming of the SASB method and is shown to improve the spatial resolution of the beamformed image. This algorithm is also adapted to, and tested on, vertical two-layer structures with two distinct SOS's, through simulations and measurements on an in-house phantom. The premise is that two layers can simulate a fat/muscle or fat/organ anatomy. Spatial resolution is shown to improve with the SOS correction. Future work will investigate whether that this two-layer SOS estimation and correction algorithm will similarly improve the imaging quality in vivo such as abdominal ultrasound examinations of overweight patients.

Text

2016-01-05

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/56244

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/