Adaptive Beamforming for Medical Ultrasound Imaging

This dissertation investigates the application of adaptive beamforming for medical ultrasound imaging. The investigations have been concentrated primarily on the Minimum Variance (MV) beamformer. A broadband implementation of theMV beamformer is described, and simulated data have been used to demonstrate the performance. The MV beamformer has been applied to different sets of ultrasound imaging sequences; synthetic aperture ultrasound imaging and plane wave ultrasound imaging. And an approach for applying MV optimized apodization weights on both the transmitting and the receiving apertures is suggested. These investigations show that the MV beamformer provides a significantly reduced main-lobe width compared to the conventional delay and sum beamformer. The effects of near-field propagation and a comparison between a subband and a temporal implementation are considered. And an investigation of the influence of sound speed errors on the adaptive beamformers; MV and the Amplitude and Phase EStimation (APES) beamformer. Furthermore, the investigations of previously suggested adaptive spectral Doppler techniques are continued by additional in-vivo measurements. These investigations shows that the adaptive spectral Doppler techniques are indeed capable of providing spectrogramswith increased resolution and contrast compared to the conventional methods, based on Welch’s spectral estimator. The investigation includes measurements of both arterial and venous flow patterns, located at different depths within the human body.