Minimum variance adaptive beamforming applied to medical ultrasound imaging

Abstract

We have applied the minimum variance beam- former to medical ultrasound imaging and shown significant improvement in image quality compared to delay-and-sum. Reduced mainlobe width and suppression of sidelobes is demonstrated on both simulated and experimental RF data of closely spaced wire targets, resulting in increased resolution and contrast. The method has been applied to experimental RF data from a heart-phantom, demonstrating improved definition of the ventricular walls. We have evaluated the beamformers sensitivity to velocity errors and shown that reliable amplitude estimates are achieved if proper regular- ization is applied. I. INTRODUCTION Delay-and-sum (DAS) beamforming is the standard technique in medical ultrasound imaging. An image is formed by transmitting a narrow beam in a number of angles and dynamically delaying and summing the received signals from all channels. The large sidelobes of the DAS beamformer can be suppressed using aperture shading, resulting in increased contrast at the expense of resolution. In contrast to the predetermined shading in DAS, adaptive beamformers use the recorded wavefield to compute the aperture weights. By suppressing inter- fering signals from off-axis directions and allowing large sidelobes in directions where there is no received energy, the adaptive beamformers can increase resolution. The minimum variance (MV) adaptive beamformer (1) and subspace-based methods have mostly been studied in narrowband applications. Extensions to broadband imaging include preprocessing with focusing- and spa- tial resampling filters, allowing narrowband methods to be used on broadband data (2), (3). We have applied the MV beamformer to medical ultrasound imaging by prefocusing in the direction of the transmitted beam - as the delay-step in DAS - and replaced the summing with the MV method. Similar methods have been used by Mann and Walker (4), and Sasso and Cohen-Bacrie (5) in medical ultrasound imaging. The former use a con- strained adaptive beamformer on experimental data of a single point target and a cyst phantom demonstrating improved contrast and resolution, whereas the latter use an MV beamfomer on a simulated data-set, showing improved contrast in the final image. We demonstrate resolution improvement and sidelobe suppression on both simulated and experimental RF data of closely spaced wire targets, and show improvement in the image of a heart-phantom obtained from experimental RF data. We also evaluate robustness of the beamformer to errors in acoustic velocity, and show that reliable amplitude estimates are achieved by regularization.