Browsing by Subject "Beamforming"

The design and characterization of electromagnetic metamaterial structures and their constituent subwavelength metamaterial elements are presented. The proposed structures can be employed in beamforming and physical layer processing applications. The common approach for designing such structures involves extracting the effective medium properties of the elements, a methodology inspired by early metamaterial research. The modeling and simulation method is made computationally feasible by assuming a periodic arrangement of the elements. In the case of aperiodic structures, the periodic assumption is no longer valid, and the electromagnetic behavior cannot be predicted accurately. To get a more accurate picture, the electromagnetic properties of individual elements must be evaluated to design a metamaterial structure. In this dissertation, I outline robust steps to realize electromagnetic metamaterial structures by characterizing metamaterial elements without any periodicity assumptions. The subwavelength elements are modeled as electric and magnetic dipoles, and I use dipole-based optimization techniques to design the structures. The dipolar elements are described by their electric and magnetic polarizabilities. Polarizability extraction methods to characterize the different metamaterial elements using numerical simulations are discussed in detail.

In recent years, the coupled dipole model (CDM) has been fully developed to predict the electromagnetic behavior of metamaterial given the element polarizabilities. However, the inverse problem to arrive at the desired medium given some desired behavior is a non-linear problem and can be computationally expensive to solve. Traditionally, holographic methods are used to linearize the problem in the perturbative limits limit to make it computationally tractable. The recently introduced symphotic method solves the non-linear electromagnetic inverse problem efficiently by iteratively solving two linear systems without making any assumptions. This allows one to encode multiple operations in a volume which is not possible with standard computer-generated holography design methods. Here, the two inverse design tools- holography and symphotic are investigated under the dipole framework and validated both numerically and experimentally using different metamaterial structures and corresponding elements.

A waveguide-fed metasurface consists of an array of metamaterial elements excited by a guided mode. When the metamaterial elements are excited, they in turn leak out a portion of the energy traveling through the waveguide to free space. As such, a waveguide-fed metasurface acts as an antenna. These antennas possess a planar form factor that offers tremendous dexterity in forming prescribed radiation patterns; a capability that has led to revolutionary advances in antenna engineering, microwave imaging, flat optics, among others.

Yet, the common approach to model and design such metasurfaces relies on effective surface properties, a methodology that is inspired by initial metamaterial designs. This methodology is only applicable to periodic arrangements of elements, and the assumption that the neighboring elements are identical. In the scenarios where the metasurface consists of an aperiodic array, or the neighboring elements are significantly different, or the coupling to the waveguide structure changes; the aforementioned approaches cannot predict the electromagnetic response of the waveguide-fed metasurface. In this thesis, I have implemented a robust technique to model waveguide-fed metasurfaces without any assumption on the metamaterial elements' geometry or arrangement. The only assumption is that the metamaterial elements can be modeled as effective dipoles, which is usually the case given the subwavelength size of metamaterial elements.

Throughout this document, the simulation tool will be referred to Dipole Model. In this framework, the total response of each dipole, representing a metamaterial element, depends on the mutual interaction between elements, as well as the perturbation of the guided mode. Both effects are taken into account and, by using full-wave simulations, I have confirmed the validity of the model and the ability to predict radiation patterns that can be used for beamforming as well as for microwave imaging.

Once the capabilities of the dipole model are compared with full wave simulations of both traditional antenna designs as well as more elaborated waveguide-fed metasurfaces, I develop an analysis on the use of these metasurfaces for microwave imaging systems. These systems are used to form images of buried objects, which is crucial in security screening and synthetic aperture radar (SAR). Traditionally, the hardware needed for many imaging techniques is cumbersome, including large arrays of antennas or bulky, moving parts. However, one attractive alternative to overcome these problems is to use dynamic metasurface antennas. By quickly varying the radiation patterns generated by these antennas, enough diverse measurements can be made in order to produce high quality images in a fraction of the time.

The compact size and speed come with a trade-off: a computationally intensive optical inverse problem has to be solved, which has so far prohibited these antennas from enjoying widespread use. I address this problem by reformulating the problem to make it similar to a SAR scenario, for which fast image reconstruction algorithms already exist. By adapting an algorithm known as the Range Migration to be compatible with these metasurfaces, I can cut down on real-time computation significantly. The computer simulations performed are highly promising for the field of microwave imaging, since it is demonstrated that diffraction-limited images can be acquired in a fraction of the time, in comparison with other imaging techniques.

Beamforming of ultrasound signals in the presence of clutter, or partial aperture blockage by an acoustic obstacle can lead to reduced visibility of the structures of interest and diminished diagnostic value of the resulting image. We propose new beamforming methods to recover the quality of ultrasound images under such challenging conditions. Of special interest are the signals from large apertures, which are more susceptible to partial blockage, and from commercial matrix arrays that suffer from low sensitivity due to inherent design/hardware limitations. A coherence-based beamforming method designed for suppressing the in vivo clutter, namely Short-lag Spatial Coherence (SLSC) Imaging, is first implemented on a 1-D array to enhance visualization of liver vasculature in 17 human subjects. The SLSC images show statistically significant improvements in vessel contrast and contrast-to-noise ratio over the matched B-mode images. The concept of SLSC imaging is then extended to matrix arrays, and the first in vivo demonstration of volumetric SLSC imaging on a clinical ultrasound system is presented. The effective suppression of clutter via volumetric SLSC imaging indicates it could potentially compensate for the low sensitivity associated with most commercial matrix arrays. The rest of the dissertation assesses image degradation due to elements blocked by ribs in a transthoracic scan. A method to detect the blocked elements is demonstrated using simulated, ex vivo, and in vivo data from the fully-sampled 2-D apertures. The results show that turning off the blocked elements both reduces the near-field clutter and improves visibility of anechoic/hypoechoic targets. Most importantly, the ex vivo data from large synthetic apertures indicates that the adaptive weighing of the non-blocked elements can recover the loss of focus quality due to periodic rib structure, allowing large apertures to realize their full resolution potential in transthoracic ultrasound.

Coronary heart disease contributed to approximately one in four deaths in the United States in 2014, and is caused by a restriction of blood flow to myocardial tissue. Stress echocardiography is a clinical technique used to assess myocardial ischemia by observing changes (or lack thereof) in ventricular wall motion in response to cardiac stress. The American Society of Echocardiography (ASE) recommends that left ventricle functionality be quantified using a 16 or 17 segment model of the left ventricle (LV). To properly assess the function of the ventricle, clear endocardial border delineation is necessary.

However, an increasing prevalence of obesity has been linked to a rise in the number of unreadable ultrasound scans. Image degradation is attributed to tissue inhomogeneities and subcutaneous fat layers, giving rise to phase aberration errors and acoustical clutter from near-field reverberation. In the event that two or more segments are inadequately visualized, the ASE recommends the use of contrast agents. Though contrast agents are effective, they are invasive and increase the procedure time and costs.

Recent work has shown that clutter can be suppressed using a novel image reconstruction technique based on the second order statistics of ultrasound echoes called short-lag spatial coherence (SLSC). Unlike conventional B-mode imaging, which forms images of the echo magnitude, SLSC forms images of the spatial coherence of the echo. By suppressing clutter, a sufficient improvement in the visualization of the endocardial border could minimize the need for contrast agents and potentially reduce the level of expertise necessary to interpret images. Though promising in preliminary studies, SLSC has a high computational demand that limited previous studies to offline image reconstruction. The goal of this research was to implement spatial coherence imaging in real-time, and to assess its performance in echocardiography.

First, the existing spatial coherence estimation methodology was investigated, and three computationally efficient modifications were proposed: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods were implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator was found to have lower variance than the currently used average correlation estimator. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4 and 20-fold in vivo with a downsample factor of 2.

Spatial coherence estimation techniques were also expanded to 2D matrix array transducers. SLSC images generated with a 2D array yielded superior contrast-to-noise ratio (CNR) and texture signal-to-noise ratio (SNR) measurements over SLSC images made on a corresponding 1D array and over B-mode imaging. SLSC images generated with square subapertures were found to be superior to SLSC images generated with subapertures of equal surface area that spanned the whole array in one dimension. Subaperture beamforming was found to have little effect on SLSC imaging performance for subapertures up to 8x8 elements in size on a 64x64 element transducer. Additionally, the use of 8x8, 4x4, and 2x2 element subapertures provided an 8, 4, and 2 times improvement in channel SNR along with a 2640-, 328-, and 25-fold reduction in computation time, respectively.

The improved spatial coherence estimation methodology was implemented using a GPU-based software beamformer to develop a real-time SLSC imaging system suitable for echocardiography. The system went through several iterations, with the final form consisting of a stand-alone CUDA C++ library for GPU-based beamforming, and a second CUDA C++ library to interface a research ultrasound scanner with the first. The resulting system was capable of live spatial coherence imaging at more than 30 frames per second, a rate sufficient for echocardiography.

The system was then used in a clinical study to image 15 stress echocardiography patients with poor image quality. A fundamental and harmonic imaging study was conducted. The latter study, which had greater clinical significance, was an assessment of the visibility of 17 LV segments using conventional tissue harmonic imaging (THI) and harmonic spatial coherence imaging (HSCI). A cardiologist rated the visibility of each of 17 LV segments as 0=invisible, 1=poorly visualized, or 2=well visualized, where scores of 0 and 1 indicated a need for contrast agent. There was a clear superiority of HSCI over THI in a comparison of overall segment scores (p < 0.0001 by symmetry test unadjusted for clustering). When comparing the number of segments with clinically acceptable image quality per patient, HSCI again showed superiority over THI (p < 0.0001 by McNemar test adjusted for clustering). In one patient, HSCI improved visualization sufficiently to eliminate the need for contrast agents altogther. These results indicate that spatial coherence imaging may provide sufficient improvements in LV wall visualization in certain patients to proceed without contrast agents.

The research in spatial coherence estimation techniques also proved fruitful in other areas of ultrasound imaging, such as ultrasound molecular imaging (USMI). USMI is accomplished by detecting microbubble (MB) contrast agents that have bound to specific biomarkers, and can be used for the early detection of cancer. However, USMI in humans is challenging because of the signal degradation caused by the presence of heterogenous subcutaneous tissue. In a phantom and in vivo study, USMI performance was assessed using conventional contrast-enhanced ultrasound (CEUS) imaging and SLSC-CEUS. In a USMI-mimicking phantom, SLSC-CEUS was found to be more robust than DAS to additive thermal noise, with a 9 dB and 15 dB SNR improvement without and with -6 dB thermal noise, respectively. USMI performance was also measured in vivo using VEGFR2-targeted MBs in mice with subcutaneous human hepatocellular carcinoma tumors. SLSC-CEUS improved the SNR in each of 10 tumors by an average of 65%, corresponding to 4.3 dB SNR. These results indicate that the SLSC beamformer is well-suited for USMI applications because of its high sensitivity and robust properties.

These studies are a demonstration of the feasibility of real-time spatial coherence imaging using current technology, and an exposition of its utility in medical ultrasound imaging.

This dissertation investigates the use of large coherent ultrasound apertures to improve diagnostic image quality for deep clinical targets. The current generation of ultrasound scanners restrict aperture size and geometry based on hardware limitations and field of view requirements at the expense of image quality. This work posits that, without these restrictions, ultrasound could be used for higher quality non-invasive imaging. To support this claim, an experimental device was constructed to acquire in vivo liver images with a synthetic aperture spanning at least 35 degrees at a radius of 10.2 cm with a scan time under one second. Using a 2.5 MHz commercial matrix array with the device, a lateral resolution of 0.45 mm at a depth of 11.6 cm was achieved, surpassing the capabilities of existing commercial systems. This work formed the basis for an in-depth investigation of the clinical promise of large aperture imaging.

Ex vivo study of volumetric imaging through the human abdominal wall demonstrated the ability of large apertures to improve target detectability at depth by significantly increasing lateral resolution, even in the presence of tissue-induced aberration and reverberation. For various abdominal wall samples studied, full-width at half-maximum resolution was increased by 1.6 to 4.3 times using a 6.4 cm swept synthetic aperture compared to conventional imaging. Harmonic plane wave imaging was shown to limit the impact of reverberation clutter from the tissue layer and produce images with the highest target detectability, up to a 45.9% improvement in contrast-to-noise ratio (CNR) over fundamental imaging. This study was corroborated by simulation of a 10 cm concave matrix array imaging through an abdominal wall based on the Visible Human Project data set. The large aperture data were processed in several ways, including in their entirety as a fully populated large array as well as mimicking the swept synthetic aperture configuration. Image quality improved with growing aperture size up to the extent of the simulated array. Contrast was increased by up to 8.4 dB and CNR by 15.5% for the full aperture compared to a 1.92 cm length array in addition to the significantly improved resolution. While the magnitude of aberration was estimated to be 25.4 ns in the simulation, reverberation clutter seemed to be the dominant source of image degradation in these studies.

Selected nonlinear beamforming methods were applied to both data sets to produce images with reduced acoustic clutter. Spatial compounding was applied to the large aperture to improve contrast by 13.4 dB and CNR by 54.4%, greatly increasing the visibility of the anechoic lesion target. It is hypothesized that the variation in the acoustic properties of the abdominal wall across the extent of the large aperture led to variations in the observed clutter that were favorable for spatial compounding. Short-lag spatial coherence (SLSC) imaging applied to the synthetic aperture images also improved image quality, but had a smaller impact for the large array data than has been previously described in the literature. Strongly suppressed spatial coherence was observed across the large array and may have limited the ability of SLSC to reduce the impact of clutter in the images.

In summary, by combining advanced beamforming methods with a large aperture extent, high quality images were produced in challenging imaging environments. This work suggests that development of a large coherent ultrasound system would benefit patients whose needs cannot be met with current technologies due to insufficient resolution at depth.