We have applied the minimum variance (MV) adaptive beamformer to medical ultrasound imaging and shown significant improvement in image quality compared to delay-and-sum (DAS). We demonstrate reduced main-lobe width and suppression of sidelobes on both simulated and experimental RF data of closely spaced wire targets, which gives potential contrast and resolution enhancement in medical images. The method is applied to experimental RF data from a heart phantom, in which we show increased resolution and improved definition of the ventricular walls. A potential weakness of adaptive beamformers is sensitivity to errors in the assumed wavefield parameters. We look at two ways to increase robustness of the proposed method; spatial smoothing and diagonal loading. We show that both are controlled by a single parameter that can move the performance from that of a MV beamformer to that of a DAS beamformer. We evaluate the sensitivity to velocity errors and show that reliable amplitude estimates are achieved while the mainlobe width and sidelobe levels are still significantly lower than for the conventional beam-former.

Frequency-dependent attenuation typically obeys an empirical power law with an exponent ranging from 0 to 2. The standard time-domain partial differential equation models can describe merely two extreme cases of frequency-independent and frequency-squared dependent attenuations. The otherwise nonzero and nonsquare frequency dependency occurring in many cases of practical interest is thus often called the anomalous attenuation. In this study, a linear integro-differential equation wave model was developed for the anomalous attenuation by using the space-fractional Laplacian operation, and the strategy is then extended to the nonlinear Burgers equation. A new definition of the fractional Laplacian is also introduced which naturally includes the boundary conditions and has inherent regularization to ease the hypersingularity in the conventional fractional Laplacian. Under the Szabo’s smallness approximation, where attenuation is assumed to be much smaller than the wave number, the linear model is found consistent with arbitrary frequency power-law dependency.

Recently, significant improvement in image resolution has been demonstrated by applying adaptive beamforming to medical ultrasound imaging. In this paper, we have used the minimum-variance beamformer to show how the low sidelobe levels and narrow beamwidth of adaptive methods can be used, not only to increase resolution, but also to enhance imaging in several ways. By using a minimum-variance beamformer instead of delay-and-sum on reception, reduced aperture, higher frame rates, or increased depth of penetration can be achieved without sacrificing image quality. We demonstrate comparable resolution on images of wire targets and a cyst phantom obtained with a 96-element, 18.5-mm transducer using delay-and-sum, and a 48-element, 9.25-mm transducer using minimum variance. To increase frame rate, fewer and wider transmit beams in combination with several parallel receive beams may be used. We show comparable resolution to delay-and-sum using minimum variance, 1/4th of the number of transmit beams and 4 parallel receive beams, potentially increasing the frame rate by 4. Finally, we show that by lowering the frequency of the transmitted beam and beamforming the received data with the minimum variance beamformer, increased depth of penetration is achieved without sacrificing lateral resolution.

One of the most promising techniques for limiting complexity for real-time 3-D ultrasound systems is to use sparse 2-D layouts. For a given number of channels, optimization of performance is desirable to ensure high quality volume images. To find optimal layouts, several approaches have been followed with varying success. The most promising designs proposed are Vernier arrays, but also these suffer from high peaks in the sidelobe region compared with a dense array. In this work, we propose new methods based on the principles of suppression of grating lobes to form symmetric and non-symmetric regular sparse periodic and radially periodic designs. The proposed methods extend the concept of sparse periodic layouts by exploiting either an increased number of symmetry axes or radial symmetry. We also introduce two new strategies to form designs with nonoverlapping elements. The performance of the new layouts range from the performance of Vernier arrays to almost that of dense arrays. Our designs have simplicity in construction, flexibility in the number of active elements, and the possibility of trade off sidelobe peaks against sidelobe energy.

The coherence factor (CF) is used for aberration correction and sidelobe suppression in ultrasound imaging. Unfortunately, it suffers from artifacts when the SNR is low. We show how the CF can be interpreted as an implementation of the Wiener postfilter for a delay-and-sum beamformer. In addition, we show that a minimum-variance, distortionless-response beamformer followed by CF weighting can be interpreted as an implementation of the Wiener beamformer. These interpretations provide us with a theoretical framework for analyzing and improving CF-based methods. We use this theory to develop more robust implementations for both the Wiener postfilter and beamformer. The performance of these implementations is shown on simulated and real data.

Szabo’s models of acoustic attenuation [Szabo, J. Acoust. Soc. Am. 96(1), 491–500 (1994)] comply well with the empirical frequency power law involving noninteger and odd-integer exponent coefficients while guaranteeing causality, but nevertheless encounter the troublesome issues of hypersingular improper integral and obscurity in implementing initial conditions. The purpose of this paper is to ease or remove these drawbacks of the Szabo’s models via the Caputo fractional derivative concept. The positive time-fractional derivative is also introduced to include the positivity of the attenuation processes.