Aperture Domain Research Articles

Enhancing sizing accuracy in ultrasound images with an alternative ADMIRE model and dynamic range considerations

Ultrasound imaging can struggle with sizing accuracy, especially when the targets have a significantly different amplitude compared to the surrounding background. In this work, we consider the challenging task of accurately sizing hyperechoic structures, and specifically kidney stones, where accurate sizing is critical for determining medical intervention. AD-Ex, an extended alternative model of our aperture domain model image reconstruction (ADMIRE) pre-processing method, is introduced and is designed to improve clutter removal and improve sizing accuracy. We compare this method against other resolution enhancing methods such as minimum variance (MV) and generalized coherence factor (GCF), and against those methods using AD-Ex as a pre-processing tool. These methods are evaluated among patients with kidney stone disease, with the task of accurately sizing the stones against the gold standard, computed tomography (CT). Stone ROI’s were selected using contour maps as reference from which the lateral stone size was estimated. Among the in vivo kidney stone cases we processed, AD-Ex+MV had the overall lowest sizing error among the methods, with an average error of 10.8% compared to the next best method AD-Ex which had an average error of 23.4%. For reference, DAS had an average error of 82.4%. Though dynamic range was evaluated to determine optimal thresholding for sizing applications, variability between stone cases was too high for any conclusions to be drawn at this time.

Combining ADMIRE and MV to Improve Image Quality.

Aperture domain model image reconstruction (ADMIRE) is a frequency-domain, model-based beamformer, in part designed for removing reverberation and off-axis clutter. Minimum variance (MV) is alternatively designed to reduce off-axis interference and improve lateral resolution. MV is known to be less effective in high incoherent noise scenarios, and its performance in the presence of reverberation has not been evaluated. By implementing ADMIRE before MV, the benefits of both these beamformers can be achieved. In this article, the assumptions of MV are discussed, specifically their relationship to reverberation clutter. The use of ADMIRE as a preprocessing step to suppress noise from simulations with linear scanning and in vivo curvilinear kidney data is demonstrated, and both narrowband and broadband implementations of MV are applied. With optimal parameters, ADMIRE + MV demonstrated sizing improvements over MV alone by an average of 52.1% in 0-dB signal-to-clutter ratio reverberation cyst simulations and 14.5% in vivo while improving the contrast ratio compared to ADMIRE alone by an average of 15.1% in simulations and 14.0% in vivo. ADMIRE + MV demonstrated a consistent improvement compared to DAS, MV, and ADMIRE both in terms of sizing and contrast ratio.

Members of the ELMOD protein family specify formation of distinct aperture domains on the Arabidopsis pollen surface.

Pollen apertures, the characteristic gaps in pollen wall exine, have emerged as a model for studying the formation of distinct plasma membrane domains. In each species, aperture number, position, and morphology are typically fixed; across species they vary widely. During pollen development, certain plasma membrane domains attract specific proteins and lipids and become protected from exine deposition, developing into apertures. However, how these aperture domains are selected is unknown. Here, we demonstrate that patterns of aperture domains in Arabidopsis are controlled by the members of the ancient ELMOD protein family, which, although important in animals, has not been studied in plants. We show that two members of this family, MACARON (MCR) and ELMOD_A, act upstream of the previously discovered aperture proteins and that their expression levels influence the number of aperture domains that form on the surface of developing pollen grains. We also show that a third ELMOD family member, ELMOD_E, can interfere with MCR and ELMOD_A activities, changing aperture morphology and producing new aperture patterns. Our findings reveal key players controlling early steps in aperture domain formation, identify residues important for their function, and open new avenues for investigating how diversity of aperture patterns in nature is achieved.

A Real-Time, GPU-Based Implementation of Aperture Domain Model Image REconstruction.

Multipath and off-axis scattering are two of the primary mechanisms for ultrasound image degradation. To address their impact, we have proposed Aperture Domain Model Image REconstruction (ADMIRE). This algorithm utilizes a model-based approach in order to identify and suppress sources of acoustic clutter. The ability of ADMIRE to suppress clutter and improve image quality has been demonstrated in previous works, but its use for real-time imaging has been infeasible due to its significant computational requirements. However, in recent years, the use of graphics processing units (GPUs) for general-purpose computing has enabled the significant acceleration of compute-intensive algorithms. This is because many modern GPUs have thousands of computational cores that can be utilized to perform massively parallel processing. Therefore, in this work, we have developed a GPU-based implementation of ADMIRE. The implementation on a single GPU provides a speedup of two orders of magnitude when compared to a serial CPU implementation, and additional speedup is achieved when the computations are distributed across two GPUs. In addition, we demonstrate the feasibility of the GPU implementation to be used for real-time imaging by interfacing it with a Verasonics Vantage 128 ultrasound research system. Moreover, we show that other beamforming techniques, such as delay-and-sum (DAS) and short-lag spatial coherence (SLSC), can be computed and simultaneously displayed with ADMIRE. The frame rate depends upon various parameters, and this is exhibited in the multiple imaging cases that are presented. An open-source code repository containing CPU and GPU implementations of ADMIRE is also provided.

Multidimensional Clutter Filtering of Aperture Domain Data for Improved Blood Flow Sensitivity.

Singular value decomposition (SVD) is a valuable factorization technique used in clutter rejection filtering for power Doppler imaging. Conventionally, SVD is applied to a Casorati matrix of radio frequency data, which enables filtering based on spatial or temporal characteristics. In this article, we propose a clutter filtering method that uses a higher order SVD (HOSVD) applied to a tensor of aperture data, e.g., delayed channel data. We discuss temporal, spatial, and aperture domain features that can be leveraged in filtering and demonstrate that this multidimensional approach improves sensitivity toward blood flow. Further, we show that HOSVD remains more robust to short ensemble lengths than conventional SVD filtering. Validation of this technique is shown using Field II simulations and in vivo data.

Passive Cavitation Mapping by Cavitation Source Localization From Aperture-Domain Signals-Part I: Theory and Validation Through Simulations.

Passive cavitation mapping (PCM) algorithms for diagnostic ultrasound arrays based on time exposure acoustics (TEA) exhibit poor axial resolution, which is in part due to the diffraction-limited point spread function of the imaging system and poor rejection by the delay-and-sum beamformer. In this article, we adapt a method for speed of sound estimation to be utilized as a cavitation source localization (CSL) approach. This method utilizes a hyperbolic fit to the arrival times of the cavitation signals in the aperture domain, and the coefficients of the fit are related to the position of the cavitation source. Wavefronts exhibiting poor fit to the hyperbolic function are corrected to yield improved source localization. We demonstrate through simulations that this method is capable of accurate estimation of the origin of coherent spherical waves radiating from cavitation/point sources. The average localization error from simulated microbubble sources was 0.12 ± 0.12mm ( 0.15 ± 0.14λ0 for a 1.78-MHz transmit frequency). In simulations of two simultaneous cavitation sources, the proposed technique had an average localization error of 0.2mm ( 0.23λ0 ), whereas conventional TEA had an average localization error of 0.81mm ( 0.97λ0 ). The reconstructed PCM-CSL image showed a significant improvement in resolution compared with the PCM-TEA approach.

Evaluating Input Domain and Model Selection for Deep Network Ultrasound Beamforming.

Improving ultrasound B-mode image quality remains an important area of research. Recently, there has been increased interest in using deep neural networks (DNNs) to perform beamforming to improve image quality more efficiently. Several approaches have been proposed that use different representations of channel data for network processing, including a frequency-domain approach that we previously developed. We previously assumed that the frequency domain would be more robust to varying pulse shapes. However, frequency- and time-domain implementations have not been directly compared. In addition, because our approach operates on aperture domain data as an intermediate beamforming step, a discrepancy often exists between network performance and image quality on fully reconstructed images, making model selection challenging. Here, we perform a systematic comparison of frequency- and time-domain implementations. In addition, we propose a contrast-to-noise ratio (CNR)-based regularization to address previous challenges with model selection. Training channel data were generated from simulated anechoic cysts. Test channel data were generated from simulated anechoic cysts with and without varied pulse shapes, in addition to physical phantom and in vivo data. We demonstrate that simplified time-domain implementations are more robust than we previously assumed, especially when using phase preserving data representations. Specifically, 0.39- and 0.36-dB median improvements in in vivo CNR compared to DAS were achieved with frequency- and time-domain implementations, respectively. We also demonstrate that CNR regularization improves the correlation between training validation loss and simulated CNR by 0.83 and between simulated and in vivo CNR by 0.35 compared to DNNs trained without CNR regularization.

Antenna Feed Array Synthesis for Efficient Communication Systems

Accurate synthesis of antenna radiation behavior is a complementary step towards simulation in antenna systems design process. In this paper, a spherical harmonic decomposition (SHD) and coupled structure electromagnetic statistical model (CSESM) methods are hybridized and adapted for the first time, to actively synthesize radiation characteristics using antenna feed array. The problem of finding the feed array aperture size, capable of synthesizing a required field intensity distribution, within a specified region for a reflector system signaling a satellite is also addressed. Relationship that exist between the required number of elements in feed array, frequency of operation, volume of the synthesis region, and the required reflector size is theoretically benchmarked. EM radiation behavior via antenna feed array is optimally synthesized using the proposed SHD-CSESM-based method. With this approach, operation limits on the synthesis of the signal field within a test volume of a given radius is predicted. Efficiency and effectiveness of SHD-CSESM-based EM field synthesis scheme unveiled are investigated for structures in a region where feed antennas are positioned distance away (focal point) from reflector system operating at Ka band. Experimental measurement data of a circularly polarized Ka-band $2\times2$ -antenna feed array is compared with the proposed theoretical method, and results obtained demonstrate the validity of the proposed algorithm. Furthermore, for any wave number ${k}$ or frequency f, the field radiation behaviour within the sphere can be accurately synthesized using an ${N}$ order expansion and ${V} \ge (4{N}+1)/{N}$ array size. Results obtained show that the proposed synthesis method handles constrains related to both aperture domain and radiation domain. Hence, SHD-CSESM-based technique is a good candidate for EM field synthesis, with the notion of automating system design processes in the emerging and future EM field applications.

Iterative Model-Based Beamforming for High Dynamic Range Applications.

Clutter produced using bright acoustic sources can obscure weaker acoustic targets, degrading the quality of the image in scenarios with high dynamic ranges. Many adaptive beamformers seek to improve image quality by reducing these sidelobe artifacts, generating a boost in contrast ratio or contrast-to-noise ratio. However, some of these beamformers inadvertently introduce a dark region artifact in place of the strong clutter, a situation that occurs when both clutter and the underlying signal of interest are removed. We introduce the iterative aperture domain model image reconstruction (iADMIRE) method that is designed to reduce clutter while preserving the underlying signal. We compare the contrast ratio dynamic range (CRDR) of iADMIRE to several other adaptive beamformers plus delay-and-sum (DAS) to quantify the accuracy and reliability of the reported measured contrast for each beamformer over a wide range of contrast levels. We also compare all beamformers in the presence of bright targets ranging from 40 to 120 dB to observe the presence of sidelobes. In cases with no added reverberation clutter, iADMIRE had a CRDR of 75.6 dB when compared with the next best method DAS with 60.8 dB. iADMIRE also demonstrated the best performance for levels of reverberation clutter up to 0-dB signal-to-clutter ratio. Finally, iADMIRE restored underlying speckle signal in dark artifact regions while suppressing sidelobes in bright target cases up to 100 dB.

Computationally Efficient Implementation of Aperture Domain Model Image Reconstruction.

Aperture domain model image reconstruction (ADMIRE) is a useful tool to mitigate ultrasound imaging artifacts caused by acoustic clutter. However, its lengthy run-time impairs its usefulness. To overcome this drawback, we evaluated the reduced model methods with otherwise similar performance to ADMIRE. We also assessed other approaches to speed up ADMIRE, including the use of different levels of short-time Fourier transform (STFT) window overlap and examining the degrees of freedom of the model fit. In this study, we conducted an analysis of the reduced models, including those using Gram-Schmidt orthonormalization (GSO), singular value decomposition (SVD), and independent component analysis (ICA). We evaluated these reduced models using the data from simulations, experimental phantoms, and in vivo liver scans. We then tested ADMIRE's performance using full, GSO, SVD, and ICA-fourth-order blind identification (ICA-FOBI) models. The results from simulations, experimental phantoms, and in vivo data indicate that a model reduced using the ICA-FOBI method is the most promising for accelerating ADMIRE implementation. In the in vivo liver data, the improvements in contrast relative to delay-and-sum (DAS) using a full model, GSO, SVD, and ICA-FOBI models are 6.29 ± 0.25 dB, 11.88 ± 0.90 dB, 9.01 ± 0.67 dB, and 6.36 ± 0.27 dB, respectively; whereas, the contrast-to-noise ratio (CNR) improvement values in the same order are 0.04 ± 0.06 dB, -1.70 ± 0.17 dB, -1.51 ± 0.19 dB, and 0.12 ± 0.07 dB, respectively. The implementation of ADMIRE using the reduced model methods can decrease ADMIRE's computational complexity over three orders of magnitude. The use of a 50% STFT window overlap reduces ADMIRE's serial run time by more than one order of magnitude without any remarkable loss of image quality, when compared to the use of a 90% window overlap used previously. Based on these findings, a combination of the ICA-FOBI model and the use of a 50% STFT window overlap makes the ADMIRE algorithm more computationally efficient.

Multi-covariate Imaging of Sub-resolution Targets.

Conventional B-mode ultrasound imaging assumes that targets consist of collections of point scatterers. Diffraction, however, presents a fundamental limit on a scanner's ability to resolve individual scatterers in most clinical imaging environments. Well-known optics and ultrasound literature has characterized these diffuse scattering targets as spatially incoherent and statistically stationary. In this paper, we apply a piecewise-stationary statistical model to diffuse scattering targets, in which the covariance of backscattered echoes can be described as the linear superposition of constituent components corresponding to echoes from distinct spatial regions in the field. Using this framework, we present Multi-covariate Imaging of Sub-resolution Targets (MIST), a novel estimation-based method to image the statistical properties of diffuse scattering targets, based on a decomposition of aperture domain spatial covariance. The mathematical foundations of the estimator are analytically derived, and MIST is evaluated in phantom, simulation, and in vivo studies, demonstrating consistent improvements in contrast-to-noise ratio and speckle statistics across imaging targets, without an apparent loss in resolution.

Advanced beamforming for improved functional assessment in echocardiography

Echocardiography is one of the most used medical imaging exams. The data from these exams are often used to compute quantitative metrics of cardiac health including measures such as the global longitudinal strain (GLS) or ejection fraction. Metrics related to blood flow are also derived from echocardiography data. These metrics have great potential because ideally, they provide quantitative biomarkers to monitor cardiac function over time and compare patient function to population values. Unfortunately, echocardiography data is often severely corrupted by various forms of acoustic clutter including wavefront aberration, reverberation and off-axis scattering from bright structures like the ribs and lungs. These sources of clutter degrade ultrasound image quality and corrupt the ability to derive reliable quantitative biomarkers of cardiac function. To resolve problems like these, we have been developing non-linear (mathematically) beamformers. These include our aperture domain model image reconstruction (ADMIRE) beamformer and, more recently, our deep neural network beamformer. We have shown that these beamformers are able to reduce errors related to wavefront aberration, reverberation and off-axis scattering, and also that the ADMIRE beamformer can eliminate the underestimation of global longitudinal strain caused by high levels of stationary reverberation caused by the chest wall.

Feasibility of non-linear beamforming ultrasound methods to characterize and size kidney stones.

PurposeUltrasound methods for kidney stone imaging suffer from poor sensitivity and size overestimation. The study objective was to demonstrate feasibility of non-linear ultrasound beamforming methods for stone imaging, including plane wave synthetic focusing (PWSF), short-lag spatial coherence (SLSC) imaging, mid-lag spatial coherence (MLSC) imaging with incoherent compounding, and aperture domain model image reconstruction (ADMIRE).Materials and methodsThe ultrasound techniques were evaluated in an in vitro kidney stone model and in a pilot study of 5 human stone formers (n = 6 stones). Stone contrast, contrast-to-noise ratio (CNR), sizing, posterior shadow contrast, and shadow width sizing were compared among the different techniques and to B-mode. CT imaging within 60 days was considered the gold standard stone size. Paired t-tests using Bonferroni correction were performed to evaluate comparing each technique with B-mode.ResultsMean CT measured stone size was 6.0mm (range 2.9–12.2mm) with mean skin-to-stone distance 10.2cm (range 5.4–16.3cm). Compared to B-mode, stone contrast was best with ADMIRE (mean +12.2dB), while SLSC and MLSC showed statistically improved CNR. Sizing was best with ADMIRE (mean +1.3mm error), however this was not significantly improved over B-mode (+2.4mm). PWSF performed similarly to B-mode for stone contrast, CNR, SNR, and stone sizing. In the in vitro model, the shadow contrast was highest with ADMIRE (mean 10.5 dB vs 3.1 dB with B-mode). Shadow sizing was best with SLSC (mean error +0.9mm ± 2.9), however the difference compared to B-mode was not significant.ConclusionsThe detection and sizing of stones are feasible with advanced beamforming methods with ultrasound. ADMIRE, SLSC, and MLSC hold promise for improving stone detection, shadow contrast, and sizing.

A Robust Method for Ultrasound Beamforming in the Presence of Off-Axis Clutter and Sound Speed Variation

Previously, we introduced a model-based beamforming algorithm to suppress ultrasound imaging artifacts caused by clutter sources, such as reverberation and off-axis scattering. We refer to this method as aperture domain model image reconstruction (ADMIRE). In this study, we evaluated the algorithm’s limitations and ability to suppress off-axis energy using Field II-based simulations, experimental phantoms and in vivo data acquired by a Verasonics ultrasound system with a curvilinear transducer (C5-2). We compared image quality derived from a standard delay-and-sum (DAS) beamformer, DAS with coherence factor (CF) weighting, ADMIRE and ADMIRE plus CF weighting. Simulations, phantoms and in vivo scan results demonstrate that ADMIRE substantially suppresses off-axis energy, while preserving the spatial resolution of standard DAS beamforming. We also observed that ADMIRE with CF weighting further improves some aspects of image quality. We identified limitations of ADMIRE when suppressing off-axis clutter in the presence of strong scattering, and we suggest a solution. Finally, because ADMIRE is a model-based beamformer, we used simulated phantoms to test the performance of ADMIRE under model-mismatch caused by gross sound speed deviation. The impact of sound speed errors largely mimics DAS beamforming, but ADMIRE never does worse than DAS itself in resolution or contrast. As expected the CF weighting used as a post processing technique provides a boost in contrast but decreases CNR and speckle SNR. The results indicate that ADMIRE is robust in terms of model-mismatch caused by sound speed variation, especially when the actual sound speed is slower than the assumed sound speed. As an example, the image contrast obtained using DAS, DAS + CF, ADMIRE and ADMIRE + CF in the presence of −5% gross sound speed error are 24.9 ± 0.71 dB, 39.1 ± 1.2 dB, 43.2 ± 2.3 dB and 52.5 ± 2.9 dB, respectively.

MP63-01 FEASIBILITY OF NEXT GENERATION NON-LINEAR BEAMFORMING ULTRASOUND METHODS TO CHARACTERIZE AND SIZE KIDNEY STONES

You have accessJournal of UrologyImaging/Radiology: Uroradiology IV1 Apr 2018MP63-01 FEASIBILITY OF NEXT GENERATION NON-LINEAR BEAMFORMING ULTRASOUND METHODS TO CHARACTERIZE AND SIZE KIDNEY STONES Ryan Hsi, Siegfried Schlunk, Jaime Tierney, Rebecca Jones, Mark George, Pranav Karve, Ravindra Duddu, and Brett Byram Ryan HsiRyan Hsi More articles by this author , Siegfried SchlunkSiegfried Schlunk More articles by this author , Jaime TierneyJaime Tierney More articles by this author , Rebecca JonesRebecca Jones More articles by this author , Mark GeorgeMark George More articles by this author , Pranav KarvePranav Karve More articles by this author , Ravindra DudduRavindra Duddu More articles by this author , and Brett ByramBrett Byram More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.2024AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Advanced ultrasound beamforming methods for imaging kidney stones may help address the sensitivity and size overestimation problems with standard B-mode ultrasound. The study objective was to demonstrate feasibility of advanced ultrasound beamforming methods including plane wave synthetic focusing (PWSF), short-lag spatial coherence (SLSC) imaging, mid-lag spatial coherence (MLSC) imaging with incoherent compounding, and aperture domain model image reconstruction (ADMIRE). METHODS The ultrasound techniques were evaluated using a research-based ultrasound system applied to an in vitro kidney stone model (n=12, 4 and 8cm depths) and in a pilot study of human stone formers (n=5). Stone diameter sizing, shadow contrast, and stone contrast were compared among the different techniques and to B-mode. CT measurements were used to determine true stone size in the pilot study. Analysis of variance was used to analyze the differences among group means, and t-test when comparing to B-mode, with p<0.05 considered significant. RESULTS All stones were detectable with each method. In the in vitro study, MLSC performed best compared to B-mode for mean stone contrast (31.7 dB vs 14.7 dB, p<0.0025). On average, B-mode sizing error ± SD was >1mm (1.2±1.1 mm), while those for PWSF, ADMIRE, and MLSC were <1mm (-0.3±2.9mm, 0.6±0.8, 0.8±0.8, respectively). The mean posterior stone shadow contrast was highest with ADMIRE overall (ptrend=0.008), and when comparing between ADMIRE and B-mode (8.0 dB vs 2.1 dB, respectively; p=0.0131). In the pilot clinical study (Figure), mean stone contrast was best with ADMIRE and MLSC than with B mode (28.5 dB and 27.8 dB vs 18.1dB, respectively; ptrend=0.002). Mean sizing error was best with ADMIRE (+1.2mm), however there was no statistically significant difference when compared with B mode (+2.7mm). CONCLUSIONS The detection and sizing of stones are feasible with advanced beamforming methods with ultrasound. ADMIRE and MLSC hold promise for improving stone contrast, shadow contrast, and reducing sizing error. Future work will include imaging a broader population of human stone formers. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e840-e841 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Ryan Hsi More articles by this author Siegfried Schlunk More articles by this author Jaime Tierney More articles by this author Rebecca Jones More articles by this author Mark George More articles by this author Pranav Karve More articles by this author Ravindra Duddu More articles by this author Brett Byram More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

The Impact of Model-Based Clutter Suppression on Cluttered, Aberrated Wavefronts.

Recent studies reveal that both phase aberration and reverberation play a major role in degrading ultrasound image quality. We previously developed an algorithm for suppressing clutter, but we have not yet tested it in the context of aberrated wavefronts. In this paper, we evaluate our previously reported algorithm, called aperture domain model image reconstruction (ADMIRE), in the presence of phase aberration and in the presence of multipath scattering and phase aberration. We use simulations to investigate phase aberration corruption and correction in the presence of reverberation. As part of this paper, we observed that ADMIRE leads to suppressed levels of aberration. In order to accurately characterize aberrated signals of interest, we introduced an adaptive component to ADMIRE to account for aberration, referred to as adaptive ADMIRE. We then use ADMIRE, adaptive ADMIRE, and conventional filtering methods to characterize aberration profiles on in vivo liver data. These in vivo results suggest that adaptive ADMIRE could be used to better characterize a wider range of aberrated wavefronts. The aberration profiles' full-width at half-maximum of ADMIRE, adaptive ADMIRE, and postfiltered data with 0.4- mm-1 spatial cutoff frequency are 4.0 ± 0.28 mm, 2.8 ± 1.3 mm, and 2.8 ± 0.57 mm, respectively, while the average root-mean square values in the same order are 16 ± 5.4 ns, 20 ± 6.3 ns, and 19 ± 3.9 ns, respectively. Finally, because ADMIRE suppresses aberration, we perform a limited evaluation of image quality using simulations and in vivo data to determine how ADMIRE and adaptive ADMIRE perform with and without aberration correction.

Pseudononlinear ultrasound simulation approach for reverberation clutter.

Multipath scattering, or reverberation, takes a substantial toll on image quality in many clinical exams. We have suggested a model-based solution to this problem, which we refer to as aperture domain model image reconstruction (ADMIRE). For ADMIRE to work well, it must be trained with precisely characterized data. To solve this specific problem and the general problem of efficiently simulating reverberation, we propose an approach to simulate reverberation with linear simulation tools. Our simulation method defines total propagation time, first scattering site, and a final scattering site. We use a linear simulation package, such as Field II, to simulate scattering from the final site and then shift the simulated wavefront later in time based on the total propagation time and the geometry of the first scattering site. We validate our simulations using theoretical descriptions of clutter in the literature and data acquired from ex vivo tissue. We found that ex vivo tissue clutter had a mean speckle SNR of [Formula: see text], which we could simulate with about 2 scatterers per resolution cell. Axial clutter distributions drawn from an exponential distribution with a mean of 5mm and at least 0.5 scatters per resolution cell resulted in clutter that was statistically indistinguishable from the van Cittert-Zernike behavior predicted by literature.

Monopulse time‐modulated antenna array using iterative Fourier technique

SummaryThe iterative Fourier technique (IFT) is applied to design monopulse radar tracking system using time‐modulated linear antenna array (TMLA). IFT is used to modify the time sequences of the radio‐frequency switches connected to the antennas to generate sum and difference patterns with suppressed interference‐plus‐noise signal while constraining the power losses associated with side‐band radiation (SBR). The time modulation allows quick and precise control of the excitation distribution, which increases the tracking accuracy. To obtain best angle sensitivity, the article computes the tradeoff among side‐lobe level (SLL), half power beam width, directivity, and dynamic efficiency. The approach is proved successful to handle several design constraints through adaption in radiation domain as well as in aperture domain. Authors illustrate additional representative TMLA examples where the time sequences of the selected elements are prefixed to enhance the dynamic efficiency and directivity for different SLL and side‐band level (SBL). Application of IFT saves the computational cost significantly with respect to existing state‐of‐the‐art optimization techniques. Introduction of the symmetric switching sequences simplifies the feed network greatly. The proposed design solution is validated with a fabricated TMLA prototype consisting of two time‐switched printed dipoles with microstrip via‐hole balun at 2.45 GHz. Copyright © 2016 John Wiley &amp; Sons, Ltd.

A model and regularization scheme for ultrasonic beamforming clutter reduction

Acoustic clutter produced by off-axis and multipath scattering is known to cause image degradation, and in some cases these sources may be the prime determinants of in vivo image quality. We have previously shown some success addressing these sources of image degradation by modeling the aperture domain signal from different sources of clutter, and then decomposing aperture domain data using the modeled sources. Our previous model had some shortcomings including model mismatch and failure to recover B-Mode speckle statistics. These shortcomings are addressed here by developing a better model and by using a general regularization approach appropriate for the model and data. We present results with L1 (lasso), L2 (ridge), and L1/L2 combined (elastic-net) regularization methods. We call our new method aperture domain model image reconstruction (ADMIRE). Our results demonstrate that ADMIRE with L1 regularization, or weighted toward L1 in the case of elastic-net regularization, have improved image quality. L1 by itself works well, but additional improvements are seen with elastic-net regularization over the pure L1 constraint. On in vivo example cases, L1 regularization showed mean contrast improvements of 4.6 and 6.8 dB on fundamental and harmonic images, respectively. Elastic net regularization (α = 0.9) showed mean contrast improvements of 17.8 dB on fundamental images and 11.8 dB on harmonic images. We also demonstrate that in uncluttered Field II simulations the decluttering algorithm produces the same contrast, contrast-tonoise ratio, and speckle SNR as normal B-mode imaging, demonstrating that ADMIRE preserves typical image features.

Equivalence of time and aperture domain additive noise in ultrasound coherence.

Ultrasonic echoes backscattered from diffuse media, recorded by an array transducer and appropriately focused, demonstrate coherence predicted by the van Cittert-Zernike theorem. Additive noise signals from off-axis scattering, reverberation, phase aberration, and electronic (thermal) noise can all superimpose incoherent or partially coherent signals onto the recorded echoes, altering the measured coherence. An expression is derived to describe the effect of uncorrelated random channel noise in terms of the noise-to-signal ratio. Equivalent descriptions are made in the aperture dimension to describe uncorrelated magnitude and phase apodizations of the array. Binary apodization is specifically described as an example of magnitude apodization and adjustments are presented to minimize the artifacts caused by finite signal length. The effects of additive noise are explored in short-lag spatial coherence imaging, an image formation technique that integrates the calculated coherence curve of acquired signals up to a small fraction of the array length for each lateral and axial location. A derivation of the expected contrast as a function of noise-to-signal ratio is provided and validation is performed in simulation.