Delay-and-sum Research Articles

Sub-wavelength lateral detection of tissue-approximating masses using an ultrasonic metamaterial lens

Practically applied techniques for ultrasonic biomedical imaging employ delay-and-sum (DAS) beamforming which can resolve two objects down to 2.1λ within the acoustic Fresnel zone. Here, we demonstrate a phononic metamaterial lens (ML) for detection of laterally subwavelength object features in tissue-like phantoms beyond the phononic crystal evanescent zone and Fresnel zone of the emitter. The ML produces metamaterial collimation that spreads 8x less than the emitting transducer. Utilizing collimation, 3.6x greater lateral resolution beyond the Fresnel zone limit was achieved. Both hard objects and tissue approximating masses were examined in gelatin tissue phantoms near the Fresnel zone limit. Lateral dimensions and separation were resolved down to 0.50λ for hard objects, with tissue approximating masses slightly higher at 0.73λ. The work represents the application of a metamaterial for spatial characterization, and subwavelength resolution in a biosystem beyond the Fresnel zone limit.

Damage detection of composite plate based on an improved DAS algorithm by time difference due to anisotropy

This paper proposes a damage detection method based on an improved DAS imaging algorithm by introducing time difference due to anisotropy of composite material. First, the finite element characteristic frequency method is used to obtain the dispersion curve of the composite plate, and the validity of the dispersion curve is verified. Next, the average phase velocity of the Lamb wave at mixed modes in the composite plate is obtained by two-dimensional Fourier transform (2-D FFT). The mixed modal group velocity is calculated according to the corresponding phase velocity, the mean change rate of the phase velocity and the dispersion curve obtained by simulation. The time difference due to anisotropy of composite material is investigated, and the damage location is estimated by the delay-and-sum (DAS) imaging algorithm. Experiments on carbon fiber multilayer composite plates verify the effectiveness of the proposed method.

Weighted non-linear beamformers for low cost 2-element receive ultrasound imaging system

In this paper, the development of modified beamforming methods, Filtered Delay Weight Multiply and Sum (F-DwMAS) and Filtered Delay Euclidian-Weighted Multiply and Sum (F-DewMAS), are reported. These methods were investigated on a minimum-redundancy synthetic aperture technique, called as 2 element Receive Synthetic Aperture Focusing Technique (2R-SAFT), which uses one element on transmit and two consecutive elements on receive, for reducing hardware complexity without compromising much on the image quality. The performance of the developed F-DwMAS and F-DewMAS methods were compared with Delay and Sum (DAS) and recently introduced F-DMAS beamforming methods. Notably, in the proposed methods, an additional aperture window function is designed and incorporated to the F-DMAS method. The different methods of F-DwMAS, F-DewMAS, F-DMAS and DAS were compared in terms of the resulting image quality metrics, Lateral Resolution (LR), Axial Resolution (AR), Contrast Ratio (CR) and contrast-to-noise ratio (CNR), in simulation and experiments on tissue-mimicking phantoms. Experimental results show that (F-DwMAS) and {F-DewMAS} resulted in improvements of AR by (46.32% and 23.51%), {43.56% and 17.78%}, LR by (47.81% and 30.27%), {44.26% and 26.14%} and CR by (45.68% and 17.15%), {42.16% and 9.87%} compared to those obtained using DAS and F-DMAS, respectively. However, CNR of F-DwMAS and F-DewMAS was found to be 31.19% and 21.16% less compared to DAS, but 4.89% and 18.64% more than F-DMAS, respectively. Hence, it can be concluded that the image quality improved by both F-DwMAS and F-DewMAS compared to DAS and F-DMAS. Also, between F-DwMAS and F-DewMAS, the later has the advantage of ready applicability to different acquisition schemes and settings compared to the former also having an additional advantage of better CNR compared to both F-DMAS and F-DewMAS.

Lag-Based Filtered-Delay Multiply and Sum Beamformer Combined with Two Phase-Related Factors for Medical Ultrasound Imaging.

A novel adaptive beamformer named filtered-delay multiply and sum (F-DMAS) has recently been proposed. Compared to the delay and sum (DAS) beamforming algorithm, F-DMAS can efficiently improve the resolution and contrast. However, the DAS can still be seen in the expansion of DMAS. Therefore, we rearrange the pair-wised signals in terms of lag in DMAS and then synthesize a lot of new signals. Thanks to the relationship between the spatial coherence and lag, these new signals can be thought of as sorted by the spatial coherence. Thus, we apply two phase-related factors, the polarity-based factor (PF) and the sign coherence factor (SCF), which are evaluated based on new signals, to weight the output of DMAS. The two approaches are consequently referred to as LAG-DMAS-PF and LAG-DMAS-SCF, respectively. The results show that, compared to F-DMAS and DAS, our proposed methods can improve the resolution and contrast to some extent without increasing too much computational complexity. In the comparison between LAG-DMAS-PF and LAG-DMAS-SCF, the latter has better performance, but the former can better protect image details.

Nonlinear pth root spectral magnitude scaling beamforming for clinical photoacoustic and ultrasound imaging.

A recently introduced nonlinear pth root delay-and-sum (NL-p-DAS) beamforming (BF) technique for ultrasound (US) and photoacoustic (PA) imaging, achieving better spatial and contrast resolution compared to a conventional delay and sum (DAS) technique. While the method is advantageous for better resolution, it suffers from grainy speckles and dark areas in the image mainly due to the interference of non-sinusoidal functions. In this Letter, we introduce a modified NL-p-DAS technique called nonlinear pth root spectral magnitude scaling (NL-p-SMS), which performs the pth root on the spectral magnitude instead of the temporal amplitude. We evaluated the US and PA images of NL-p-SMS against those of NL-p-DAS by comparing the axial and lateral line profiles, contrasts, and contrast-to-noise ratios (CNRs) in both phantom and in vivo imaging studies with various p values. As a result, we found that the NL-p-SMS has better axial resolution and CNR than the NL-p-DAS, and reduces the grainy speckles and dark area artifacts. We believe that, with this enhanced performance, our proposed approach could be an advancement compared to the existing nonlinear BF algorithms.

Low-complexity adaptive minimum variance ultrasound beam-former based on diagonalization

BackgroundDespite the high capability of the minimum variance (MV) beam-former in improving image quality compared to the delay and sum (DAS), its high complexity, which is due to L × L covariance matrix inversion and calculation, limits its usage for real-time applications. The complexity of MV is in the order of O(L3). MethodA low-complexity adaptive MV (LCAMV) is suggested in to reduce the complexity of the MV beam-former via the covariance matrix diagonalization. So, the proposed method focuses on two aspects: One is to reduce the complexity due to covariance matrix calculation and the other to reduce the MV complexity caused by the inversion. Thus, the MV complexity is significantly reduced, although the resulted image of LCAMV is similar to that of MV. ResultsThe LCAMV technique is applied to the simulated phantoms and real data to verify its performance and to compare it with other popular beamforming techniques. Statistical parameters of the image quality for all experiments were calculated to check the image quality. Also, the run time analysis showed that the difference between the values of the MV and LCAMV statistical image quality parameters was less than 2%, while the speed of LCAMV was about 4 times faster. ConclusionResults indicate that using LCAMV, not only the resolution and contrast are not changed significantly, but also the complexity is reduced from O(L3) to O(L×log(L)). Thus, this simple technique can be a big step towards adaptive real-time imaging.

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.

Detection and Localization of Ultrasound Scatterers Using Convolutional Neural Networks.

Delay-and-sum (DAS) beamforming is unable to identify individual scatterers when their density is so high that their point spread functions overlap. This paper proposes a convolutional neural network (CNN)-based method to detect and localize high-density scatterers, some of which are closer than the resolution limit of delay-and-sum (DAS) beamforming. A CNN was designed to take radio frequency channel data and return non-overlapping Gaussian confidence maps. The scatterer positions were estimated from the confidence maps by identifying local maxima. On simulated test sets, the CNN method with three plane waves achieved a precision of 1.00 and a recall of 0.91. Localization uncertainties after excluding outliers were ±46 [Formula: see text] (outlier ratio: 4%) laterally and ±26 [Formula: see text] (outlier ratio: 1%) axially. To evaluate the proposed method on measured data, two phantoms containing cavities were 3-D printed and imaged. For the phantom study, the training data were modified according to the physical properties of the phantoms and a new CNN was trained. On an uniformly spaced scatterer phantom, a precision of 0.98 and a recall of 1.00 were achieved with the localization uncertainties of ±101 [Formula: see text] (outlier ratio: 1%) laterally and ±37 [Formula: see text] (outlier ratio: 1%) axially. On a randomly spaced scatterer phantom, a precision of 0.59 and a recall of 0.63 were achieved. The localization uncertainties were ±132 [Formula: see text] (outlier ratio: 0%) laterally and ±44 [Formula: see text] with a bias of 22 [Formula: see text] (outlier ratio: 0%) axially. This method can potentially be extended to detect highly concentrated microbubbles in order to shorten data acquisition times of super-resolution ultrasound imaging.

GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions.

.Significance: Photoacoustic-based visual servoing is a promising technique for surgical tool tip tracking and automated visualization of photoacoustic targets during interventional procedures. However, one outstanding challenge has been the reliability of obtaining segmentations using low-energy light sources that operate within existing laser safety limits.Aim: We developed the first known graphical processing unit (GPU)-based real-time implementation of short-lag spatial coherence (SLSC) beamforming for photoacoustic imaging and applied this real-time algorithm to improve signal segmentation during photoacoustic-based visual servoing with low-energy lasers.Approach: A 1-mm-core-diameter optical fiber was inserted into ex vivo bovine tissue. Photoacoustic-based visual servoing was implemented as the fiber was manually displaced by a translation stage, which provided ground truth measurements of the fiber displacement. GPU-SLSC results were compared with a central processing unit (CPU)-SLSC approach and an amplitude-based delay-and-sum (DAS) beamforming approach. Performance was additionally evaluated with in vivo cardiac data.Results: The GPU-SLSC implementation achieved frame rates up to 41.2 Hz, representing a factor of 348 speedup when compared with offline CPU-SLSC. In addition, GPU-SLSC successfully recovered low-energy signals (i.e., ) with mean ± standard deviation of signal-to-noise ratios of (compared with with conventional DAS beamforming). When energies were lower than the safety limit for skin (i.e., for 900-nm wavelength laser light), the median and interquartile range (IQR) of visual servoing tracking errors obtained with GPU-SLSC were 0.64 and 0.52 mm, respectively (which were lower than the median and IQR obtained with DAS by 1.39 and 8.45 mm, respectively). GPU-SLSC additionally reduced the percentage of failed segmentations when applied to in vivo cardiac data.Conclusions: Results are promising for the use of low-energy, miniaturized lasers to perform GPU-SLSC photoacoustic-based visual servoing in the operating room with laser pulse repetition frequencies as high as 41.2 Hz.

The Application of an Iterative Structure to the Delay-and-Sum and the Delay-Multiply-and-Sum Beamformers in Breast Microwave Imaging.

Breast microwave imaging (BMI) is a potential breast cancer screening method. This manuscript presents a novel iterative delay-and-sum (DAS) based reconstruction algorithm for BMI. This iterative-DAS (itDAS) algorithm uses a forward radar model to iteratively update an image estimate. A variation of the itDAS reconstruction algorithm that uses the delay-multiply-and-sum (DMAS) beamformer was also implemented (the itDMAS algorithm). Both algorithms were used to reconstruct images from experimental scans of an array of 3D-printed MRI-based breast phantoms performed with a clinical BMI system. The signal-to-clutter ratio (SCR) and signal-to-mean ratio (SMR) were used to compare the performance of the itDAS and itDMAS methods to the DAS and DMAS beamformers. While no significant difference between the itDAS and itDMAS methods was observed in most images, the itDAS algorithm produced reconstructions that had significantly higher SMR than the non-iterative methods, increasing contrast by as much as 19 dB over DAS and 13 dB over DMAS. The itDAS algorithm also increased the SCR of reconstructions by up to 5 dB over DAS and 4 dB over DMAS, indicating that both high-intensity and background clutter are reduced in images reconstructed by the itDAS algorithm.

ω-k Algorithm for Sparse-Transmit Sparse-Receive Diverging Beam Synthetic Aperture Transmit Scheme

In synthetic aperture (SA) imaging reported in the ultrasound imaging literature, typically, the delay and sum (DAS) beamformer is used; however, it is computationally expensive due to the pixel-by-pixel processing performed in the time domain. Recently, the adaptation of frequency-domain beamformers for medical ultrasound SA imaging, particularly to single-element/multielement synthetic transmit aperture (STA/MSTA) schemes, has been reported. In such reports, usually, less attention is paid to reducing system complexity. Recently, a sparse-transmit sparse-receive version of diverging beam-based synthetic aperture technique (DBSAT) was shown to achieve a reduction in system complexity by using fewer parallel receive channels, yet it achieves better quality and higher frame rate than conventional focused beamforming. However, this was also demonstrated using the DAS beamformer. In this work, we aim at achieving a reduction in computational cost, in addition to a reduction in system complexity, by implementing a fast and efficient frequency-wavenumber ( ω - k ) algorithm for the sparse DBSAT scheme. In doing so, an additional novel step of recovering missing frame data due to sparse transmit is introduced, namely, projection onto elliptical sets (POES). The results from this novel combination of ω - k with POES recovery showed that it is feasible to achieve several orders of magnitude faster reconstruction compared with the standard DAS beamforming, without any compromise in the image quality and, in some cases, with improved image quality. The average value of the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) calculated from cyst at 15-mm depth obtained using the different schemes was 4.94 and 5.73 dB better when ω - k was employed instead of DAS, respectively. In addition, for the sparse data set acquired with a 50% overlap during transmit and 64 active receive elements, DAS reconstruction takes as long as ~647 s, whereas the ω - k algorithm takes only ~2 s when programmed and executed in MATLAB.

Comparison of beamforming algorithms for microphone arrays in Matlab

Subject of Research. The paper considers the main quantitative characteristics of microphone arrays in their performance analysis and beamforming algorithms applied for their study. Methods. The principal characteristics, calculation approaches and evaluations were examined. The most widespread beamforming algorithms were analyzed, such as: Delay-and-Sum (DAS), minimum variance distortionless response (MVDR), Frost’s algorithm or linearly constrained minimum variance (LCMV), generalized sidelobe canceller (GSC). The calculations and comparative analysis of the algorithms were performed in Matlab simulation environment. The following quantitative characteristics were obtained: signal-to-noise ratio, signal-interference-noise ratio, directivity index, directivity characteristics, and beamwidth. Main Results. Algorithm comparison results are presented on the example of a linear microphone array. The linearly constrained minimum variance algorithm has shown the most satisfactory results. The simulation results must be clarified by real experiments. Practical Relevance. The results of the work can be used for analysis of more complex microphone arrays and acoustic structures, such as microphone arrays with “floating” geometry and distributed microphone arrays.

Efficient Lamb-wave based damage imaging using multiple sparse Bayesian learning in composite laminates

Lamb wave techniques have been widely used for structural health monitoring (SHM) and nondestructive testing (NDT). To deal with dispersive and multimodal problems of Lamb wave signals, many signal processing methods have been developed. A spatially distributed array of piezoelectric transducers is generally adopted for both transmission and reception of Lamb waves. When imaging the damage in composite laminates, it is necessary to meet the need of processing array signals with high efficiency. In this paper, the multiple sparse Bayesian learning (M-SBL) strategy is employed for damage imaging. Multiple residual signals including damage-reflection waves are decomposed into a sparse matrix of location-based components simultaneously. An appropriate dictionary is designed to match the damage-reflection waves instead of interference waves. The key to success is to obtain the sparse matrix of weighting coefficients through the M-SBL algorithm. Damage imaging can be achieved efficiently using the delay-and-sum (DAS) method with sparse coefficients in time-domain. Results from the experiment in composite laminates demonstrate the effectiveness of the proposed method.

Eigenspace-based minimum variance beamformer combined with sign coherence factor: Application to linear-array photoacoustic imaging

Photoacoustic (PA) imaging combining the advantages of high resolution of ultrasound imaging and high contrast of optical imaging provides images with good quality. PA imaging often suffers from disadvantages such as clutter noises and decreased signal-to-noise-ratio at higher depths. One studied method to reduce clutter noises is to use weighting factors such as coherence factor (CF) and its modified versions that improve resolution and contrast of images. In this study, we combined the Eigen-space based minimum variance (EIBMV) beamformer with the sign coherence factor (SCF) and show the ability of these methods for noise reduction when they are used in combination with each other. In addition, we compared the proposed method with delay-and-sum (DAS) and minimum variance (MV) beamformers in simulated and experimental studies. The simulation results show that the proposed EIBMV-SCF method improves the SNR about 94 dB, 87.65 dB, and 62.29 dB compared to the DAS, MV, and EIBMV, respectively, and the corresponding improvements were 79.37/34.43 dB, 77.25/26.96 dB, and 33.19/25.56 dB in the ex vivo/in vivo experiments.

Simulations and human cadaver head studies to identify optimal acoustic receiver locations for minimally invasive photoacoustic-guided neurosurgery

Real-time intraoperative guidance during minimally invasive neurosurgical procedures (e.g., endonasal transsphenoidal surgery) is often limited to endoscopy and CT-guided image navigation, which can be suboptimal at locating underlying blood vessels and nerves. Accidental damage to these critical structures can have severe surgical complications, including patient blindness and death. Photoacoustic image guidance was previously proposed as a method to prevent accidental injury. While the proposed technique remains promising, the original light delivery and sound reception components of this technology require alterations to make the technique suitable for patient use. This paper presents simulation and experimental studies performed with both an intact human skull (which was cleaned from tissue attachments) and a complete human cadaver head (with contents and surrounding tissue intact) in order to investigate optimal locations for ultrasound probe placement during photoacoustic imaging and to test the feasibility of a modified light delivery design. Volumetric x-ray CT images of the human skull were used to create k-Wave simulations of acoustic wave propagation within this cranial environment. Photoacoustic imaging of the internal carotid artery (ICA) was performed with this same skull. Optical fibers emitting 750 nm light were inserted into the nasal cavity for ICA illumination. The ultrasound probe was placed on three optimal regions identified by simulations: (1) nasal cavity, (2) ocular region, and (3) 1 mm-thick temporal bone (which received 9.2%, 4.7%, and 3.8% of the initial photoacoustic pressure, respectively, in simulations). For these three probe locations, the contrast of the ICA in comparative experimental photoacoustic images was 27 dB, 19 dB, and 12 dB, respectively, with delay-and-sum (DAS) beamforming and laser pulse energies of 3 mJ, 5 mJ, and 4.2 mJ, respectively. Short-lag spatial coherence (SLSC) beamforming improved the contrast of these DAS images by up to 15 dB, enabled visualization of multiple cross-sectional ICA views in a single image, and enabled the use of lower laser energies. Combined simulation and experimental results with the emptied skull and >1 mm-thick temporal bone indicated that the ocular and nasal regions were more optimal probe locations than the temporal ultrasound probe location. Results from both the same skull filled with ovine brains and eyes and the human cadaver head validate the ocular region as an optimal acoustic window for our current system setup, producing high-contrast (i.e., up to 35 dB) DAS and SLSC photoacoustic images within the laser safety limits of a novel, compact light delivery system design that is independent of surgical tools (i.e., a fiber bundle with 6.8 mm outer diameter, 2 mm-diameter optical aperture, and an air gap spacing between the sphenoid bone and fiber tips). These results are promising toward identifying, quantifying, and overcoming major system design barriers to proceed with future patient testing.

Using the hybrid DAS-SR method for damage localization in composite plates

In this paper, the hybrid Delay-And-Sum (DAS) with Sparse Reconstruction (SR) method was further developed for damage location in composite plates. In composite materials, anisotropy leads to some challenges in using conventional damage location methods, which are developed for isotropic materials. In the hybrid DAS-SR method, the DAS and SR methods were combined as a complement of each other. To investigate the DAS-SR method for composite structures, the group velocity of the travelling wave for different directions was first measured experimentally via PZTs. The DAS and SR formulations were then modified to be compatible with the direction-dependent group velocities. The results show that this modification increases the accuracy of the DAS and SR methods for damage location in a composite plate. However, using group-velocity instead of phase-velocity in the standard SR method, causes some model mismatch and errors in the damage localization and this problem was solved by using the modified hybrid DAS-SR method. The experimental results demonstrated that the performance of the modified hybrid method for detection and location of barely visible impact damages as well as for multi-location artificial damages is better than that of the DAS and SR methods when separately used.

Adaptive and hybrid Kronecker product beamforming for far-field speech signals

This work presents a Kronecker product based methodology of frequency-domain beamforming of large sensor arrays for far-field broadband speech signals. The principal idea involves splitting up a given uniform linear array (ULA) into two smaller virtual ULAs (VULAs), using the Kronecker product. The linear system of the original ULA is bifurcated into two smaller linear systems of the VULAs. Henceforth, traditional adaptive beamformers such as the minimum-variance-distortionless-response (MVDR) beamformer may be obtained for each of the VULAs, using lesser data to estimate the statistics. The short-length beamformers, obtained from the VULAs, are finally combined by the Kronecker product to derive the full-length Kronecker product beamformer. Additionally, the VULAs allow fixed and adaptive beamforming to be implemented separately on each of them. As fixed beamformers do not employ statistical information, the Kronecker product hybrid beamformers reduce the original linear system to just a small linear system involving one VULA. Accordingly, hybrid beamformers may be implemented using traditional fixed beamformers, such as the delay-and-sum (DS) beamformer, on one VULA, and traditional adaptive beamformers, such as the MVDR, on the other. The proposed Kronecker product beamformers are observed to provide faster convergence and superior robustness with respect to the traditional beamformers.

Optimization of transmission and reconstruction parameters in angular displacement compounding using plane wave ultrasound

In ultrasound elastography, plane-wave acquisitions and angular displacement compounding (ADC) are often used and combined to allow high frame rates and to improve accuracy of lateral displacement estimates, respectively. This study investigates the performance of displacement and strain estimation for ADC as a function of; the main-to-grating-lobe-amplitude ratio which decreases as a function of steering angle; plane-wave acquisition and Delay-and-Sum (DaS)-related parameters; and grating-lobe filter cut-off frequency. Three experiments were conducted with a block phantom to test ADC performance for displacement fields of varying complexity: a lateral transducer shift, phantom rotation and phantom deformation. Experiments were repeated for four linear array transducers (pitch-to-lambda ratios between 0.6 and 1.4). Best ADC performance was found for steering angles that resulted in a theoretically derived main-to-grating-lobe-amplitude ratio of 1.7 dB for pure lateral translation and 6 dB for predominately lateral strain or rotation. Temporal filtering to reduce grating lobe signal or shifting of the receive aperture to receive angles below or above the optimal angle, as dictated by the main-to-grating-lobe-amplitude ratio, did not improve results. The accuracy of lateral displacement and strain estimates was improved by apodization in transmission and a dedicated F-number in DaS (0.75) allowing incidence angles within ± 33° in the active aperture. ADC with the optimized settings as found in this study improves the accuracy of displacements and strain estimates up to 80.7% compared to non-ADC. Compared to ADC settings described in current literature, our optimization improved the accuracy by 11.9% to 75.3% for lateral displacement and strain, and by 89.3% to 96.2% for rotation. The accuracy of ADC in rotation seemed to depend highly on plane-wave and DaS-related parameters which may explain the major improvement compared to settings in current literature. The overall improvement by optimized ADC was statistically significant compared to non-ADC (p = 0.003) and literature (p = 0.002).

Towards A Pixel-Level Reconfigurable Digital Beamforming Core for Ultrasound Imaging.

Ultrasound (US) imaging systems typically employ a single beamforming scheme which is the delay and sum (DAS) beamforming due to its reduced complexity. However, DAS results in images with limited resolution and contrast. The limitations of DAS have been overcome by, delay multiply and sum (DMAS) beamforming, making it especially preferable in cases where finer image details are required in larger depth of scans for an accurate diagnosis. But, DMAS is confined to transducer frequencies where the generated harmonics also fall in the processable frequency range of the US system. However, if US systems could provide the flexibility to reconfigure beamforming considering the restrictions of each beamforming scheme, it is possible to select the best beamforming according to the clinical requirement and system constraints. This work is a fundamental step towards enabling reconfigurable beamforming for on-the-fly selection among the DAS and DMAS beamforming schemes, with low reconfiguration overhead, specifically for each imaging scenario to aid better diagnosis. Two novel architectures are proposed, that reconfigures between DAS and DMAS beamforming as a function of transducer's center frequency with minimum additional computational overhead. The implementation results of the proposed architectures on xc7z010clg400-1 FPGA are reported. The possibilities of pixel-level beamforming reconfigurability, where the different tissue regions are beamformed with either DAS or DMAS are also shown through simulations.

Fast Focusing of Ultrasound Synthetic Aperture Imaging by Using Virtual Array and Nonuniform Fast Fourier Transform

A fast synthetic aperture (SA) focusing algorithm is proposed in this article to overcome the problem of huge computational complexity in developing high-performance SA ultrasound imaging systems. The proposed method realizes the fast focusing of SA imaging by utilizing a virtual array (VA) technique in combination with nonuniform fast Fourier transform (VA-NUFFT) method. The computational performance of the VA-NUFFT algorithm is evaluated with the computational complexity under acceptable beam errors, compared with the conventional delay-and-sum (DAS) method and the frequency-domain direct method (DM), as well as a multiple NUFFT (M-NUFFT) method. Simulation results reveal that under a beam error level less than −57.4 dB, 25 and 10 reduction ratios of entire real operations can be achieved by the VA-NUFFT at larger SA scan lines of 2048, when compared with the DAS and DM, respectively. In the key SA focusing step, i.e., the “spatial process” step, the computational load of VA-NUFFT is lower than two orders of magnitude of that of the DM. SA imaging of a phantom with four cysts is also simulated and a contrast-to-noise ratio (CNR) criterion is adopted for evaluation of imaging quality. CNR results reflect that SA images of using VA-NUFFT make almost no difference to that of DAS focusing under different signal-to-noise ratios (SNRs).