Imaging with therapeutic acoustic wavelets–short pulses enable acoustic localization when time of arrival is combined with delay and sum

—Passive acoustic mapping (PAM) is an algorithm that reconstructs the location of acoustic sources using an array of receivers. This technique can monitor therapeutic ultrasound procedures to confirm the spatial distribution and amount of microbubble activity induced. Current PAM algorithms have an excellentlateral resolution but have a poor axial resolution, making it difficult to distinguish acoustic sources within the ultrasound beams. With recent studies demonstrating that short-length and low-pressure pulses—acoustic wavelets—have the therapeutic function, we hypothesizedthat the axial resolution could be improved with a quasi-pulse-echo approach and that the resolution improvement would depend on the wavelet’s pulse length. This article describes an algorithm that resolves acoustic sources axially using time of flight and laterally using delayand-sum beamforming, which we named axial temporal position PAM (ATP-PAM). The algorithm accommodates a rapid short pulse (RaSP) sequence that can safely deliver drugs across the blood–brain barrier. We developed our algorithm with simulations (k-wave) and in vitro experiments for one-, two-, and five-cycle pulses, comparing our resolution against that of two current PAM algorithms. We then tested ATP-PAM in vivo and evaluated whether the reconstructed acoustic sources mapped to drug deliver

APES Beamforming Applied to Medical Ultrasound Imaging

As of today, sonar imaging is the most effective means of documenting the subsea environment. Existing sonar imaging systems generally rely on conventional beamforming methods to form the image. While conventional beamformers are robust and simple, they leave many of the challenges of sonar imaging unresolved. Sonar images are often degraded by noise, and the image resolution as well as the range at which useful images can be obtained is limited. This thesis addresses the use of adaptive beamforming and imaging methods applied to active sonar. The goal of an adaptive beamformer in this context is to improve the quality of the sonar image by allowing the beamformer to adapt to the situation, recognizing sources of noise and interference and suppressing them before they have the chance to contaminate the image. The desired result is an image containing more useful and correct information, less noise, and improved image resolution. Focus has been on investigating how different adaptive methods can be implemented in a practical setting, and analyzing the performance of each method. Key challenges that are addressed include coherent signals, arbitrary array geometries, computational load, and robustness. Two of the most common adaptive beamforming methods, the minimum variance distortionless response (MVDR) and the amplitude and phase estimation (APES) beamformers, are considered, as well as a low complexity variant of the adaptive MVDR beamformer. Adaptive imaging methods based on aperture coherence represent a promising class of adaptive methods, and are also considered. We conclude that in many cases, improved image quality is obtained by using adaptive beamforming methods

Real-time GPU-based adaptive beamformer for high quality ultrasound imaging

Poster Session Session P1Aa. Beam Formation: Computational Aspects And Artifact Reduction: no. P1Ac-7A real-time adaptive minimum variance (MV) beam-former realized using graphics processing units (GPUs) is presented. MV adaptive beamforming technique is attractive as it is capable of producing high quality images with narrow mainlobe width and low sidelobe level. However, because of its substantially higher computational requirements, realizing MV in real-time has been prohibitively difficult. Recent advancements in commodity GPUs have made very high performance computing possible at very affordable price. Using a commercial off-the-shelf GPU, an MV beam-former achieving real-time performance has been realized. Tradeoffs between computational throughput and image quality have been studied. Careful selection of algorithm parameters, including receive aperture and sub-aperture size, was demonstrated to be imperative for achieving real-time performance without sacrificing image qualities.published_or_final_versionThe 2011 IEEE International Ultrasonics Symposium (IUS), Orlando, FL., 18-21 October 2011. In IEEE International Ultrasonics Symposium Proceedings, 2011, p. 474-47

Ultrasound Nondestructive Evaluation (NDE) Imaging with Transducer Arrays and Adaptive Processing

This paper addresses the challenging problem of ultrasonic non-destructive evaluation (NDE) imaging with adaptive transducer arrays. In NDE applications, most materials like concrete, stainless steel and carbon-reinforced composites used extensively in industries and civil engineering exhibit heterogeneous internal structure. When inspected using ultrasound, the signals from defects are significantly corrupted by the echoes form randomly distributed scatterers, even defects that are much larger than these random reflectors are difficult to detect with the conventional delay-and-sum operation. We propose to apply adaptive beamforming to the received data samples to reduce the interference and clutter noise. Beamforming is to manipulate the array beam pattern by appropriately weighting the per-element delayed data samples prior to summing them. The adaptive weights are computed from the statistical analysis of the data samples. This delay-weight-and-sum process can be explained as applying a lateral spatial filter to the signals across the probe aperture. Simulations show that the clutter noise is reduced by more than 30 dB and the lateral resolution is enhanced simultaneously when adaptive beamforming is applied. In experiments inspecting a steel block with side-drilled holes, good quantitative agreement with simulation results is demonstrated