Matched Spatial Filter Research Articles

A unified deep network for beamforming and speckle reduction in plane wave imaging: A simulation study

Plane Wave Imaging is a fast imaging method used in ultrasound, which allows a high frame rate, but with compromised image quality when a single wave is used. In this work a learning-based approach was used to obtain improved image quality. The entire process of beamforming and speckle reduction was embedded in a single deep convolutional network, and trained with two types of simulated data. The network architecture was designed based on traditional physical considerations of the ultrasonic image formation pipe. As such, it includes beamforming with spatial matched filters, envelope detection, and a speckle reduction stage done in log-signal representation, with all stages containing trainable parameters. The approach was tested on the publicly available PICMUS datasets, achieving axial and lateral full-width-half-maximum (FWHM) resolution values of 0.22 mm and 0.35 mm respectively, and a Contrast to Noise Ratio (CNR) metric of 16.75 on the experimental datasets.

An Efficient Hybrid Beamforming Design for Massive MIMO Receive Systems via SINR Maximization Based on an Improved Bat Algorithm

Hybrid analog and digital (HAD) beamforming has been recently receiving considerable deserved attention for practical implementation on the large-scale antenna systems. Compared to fully-digital beamforming, partially-connected HAD beamforming can significantly reduce the hardware cost, complexity, and power consumption. This paper aims to mitigate interference and increase robustness against direction-of-arrival (DOA) mismatch along with lowering hardware complexity, cost, and power dissipation. To achieve these goals, a novel robust HAD beamforming receiver with partially-connected structure is proposed. It is based on methods of an improved bat algorithm (I-BA) and robust adaptive beamformers (RABs) in the digital domain. Since most of the RAB methods are sensitive to the DOA mismatch and depending on the complex weights which lead to an expensive receiver, the I-BA is proposed. In the analog part, analog phase alignment by linear searching (APALS) with sufficiently fine grid points is employed to optimize the analog beamforming matrix. The performance of the proposed I-BA is assessed using MATLAB simulation and compared with BA, and particle swarm optimization (PSO) algorithms. It shows better performance in terms of convergence speed, stability, and convergence rate. Besides, the proposed hybrid I-BA-APALS approach showed better performance compared to other proposed robust hybrid techniques, i.e., diagonal loading (DL) APALS (DL-APALS) and DL spatial matched filter (SMF) APALS (DL-SMF-APALS).

Impact of Spatial Filtering on Distortion From Low-Noise Amplifiers in Massive MIMO Base Stations

In massive multiple-input-multiple-output base stations, power consumption and cost of the low-noise amplifiers (LNAs) can be substantial because of the many antennas. We investigate the feasibility of inexpensive, power efficient LNAs, which inherently are less linear. A polynomial model is used to characterize the nonlinear LNAs and to derive the second-order statistics and spatial correlation of the distortion. We show that, with spatial matched filtering (maximum-ratio combining) at the receiver, some distortion terms combine coherently, and that the signal-to-interference-and-noise ratio of the symbol estimates therefore is limited by the linearity of the LNAs. Furthermore, it is studied how the power from a blocker in the adjacent frequency band leaks into the main band and creates distortion. The distortion term that scales cubically with the power received from the blocker has a spatial correlation that can be filtered out by spatial processing and only the coherent term that scales quadratically with the power remains. When the blocker is in free-space line-of-sight and the LNAs are identical, this quadratic term has the same spatial direction as the desired signal, and hence cannot be removed by linear receiver processing.

Decoding spoken phonemes from sensorimotor cortex with high-density ECoG grids

For people who cannot communicate due to severe paralysis or involuntary movements, technology that decodes intended speech from the brain may offer an alternative means of communication. If decoding proves to be feasible, intracranial Brain-Computer Interface systems can be developed which are designed to translate decoded speech into computer generated speech or to instructions for controlling assistive devices. Recent advances suggest that such decoding may be feasible from sensorimotor cortex, but it is not clear how this challenge can be approached best. One approach is to identify and discriminate elements of spoken language, such as phonemes. We investigated feasibility of decoding four spoken phonemes from the sensorimotor face area, using electrocorticographic signals obtained with high-density electrode grids. Several decoding algorithms including spatiotemporal matched filters, spatial matched filters and support vector machines were compared. Phonemes could be classified correctly at a level of over 75% with spatiotemporal matched filters. Support Vector machine analysis reached a similar level, but spatial matched filters yielded significantly lower scores. The most informative electrodes were clustered along the central sulcus. Highest scores were achieved from time windows centered around voice onset time, but a 500 ms window before onset time could also be classified significantly. The results suggest that phoneme production involves a sequence of robust and reproducible activity patterns on the cortical surface. Importantly, decoding requires inclusion of temporal information to capture the rapid shifts of robust patterns associated with articulator muscle group contraction during production of a phoneme. The high classification scores are likely to be enabled by the use of high density grids, and by the use of discrete phonemes. Implications for use in Brain-Computer Interfaces are discussed.

Anti-Impulse-Noise Edge Detection via Anisotropic Morphological Directional Derivatives.

Traditional differential-based edge detection suffers from abrupt degradation in performance when images are corrupted by impulse noises. The morphological operators such as the median filters and weighted median filters possess the intrinsic ability to counteract impulse noise. In this paper, by combining the biwindow configuration with weighted median filters, anisotropic morphological directional derivatives (AMDDs) robust to impulse noise are proposed to measure the local grayscale variation around a pixel. For ideal step edges, the AMDD spatial response and directional representation are derived. The characteristics and edge resolution of two kinds of typical biwindows are analyzed thoroughly. In terms of the AMDD spatial response and directional representation of ideal step edges, the spatial matched filter is used to extract the edge strength map (ESM) from the AMDDs of an image. The spatial and directional matched filters are used to extract the edge direction map (EDM). Embedding the extracted ESM and EDM into the standard route of the differential-based edge detection, an anti-impulse-noise AMDD-based edge detector is constructed. It is compared with the existing state-of-the-art detectors on a recognized image dataset for edge detection evaluation. The results show that it attains competitive performance in noise-free and Gaussian noise cases and the best performance in impulse noise cases.

Improved contrast for high frame rate imaging using coherent compounding combined with spatial matched filtering

The concept of high frame rate ultrasound imaging (typically greater than 1000 frames per second) has inspired new fields of clinical applications for ultrasound imaging such as fast cardiovascular imaging, fast Doppler imaging and real-time 3D imaging. Coherent plane-wave compounding is a promising beamforming technique to achieve high frame rate imaging. By combining echoes from plane waves with different angles, dynamic transmit focusing is efficiently accomplished at all points in the image field. Meanwhile, the image frame rate can still be kept at a high level. Spatial matched filtering (SMF) with plane-wave insonification is a novel ultrafast beamforming method. An analytical study shows that SMF is equivalent to synthetic aperture methods that can provide dynamic transmit-receive focusing throughout the field of view. Experimental results show that plane-wave SMF has better performance than dynamic-receive focusing. In this paper, we propose integrating coherent plane-wave compounding with SMF to obtain greater image contrast. By using a combination of SMF beamformed images, image contrast is improved without degrading its high frame rate capabilities. The performance of compounded SMF (CSMF) is evaluated and compared with that of synthetic aperture focusing technique (SAFT) beamforming and compounded dynamic-receive-focus (CDRF) beamforming. The image quality of different beamforming methods was quantified in terms of contrast-to-noise ratio (CNR). Our results show that the new SMF based plane-wave compounding method provides better contrast than DAS based compounding method. Also CSMF can obtain a similar contrast level to dynamic transmit-receive focusing with only 21 transmit events.

Dynamic Transmit-Receive Beamforming by Spatial Matched Filtering for Ultrasound Imaging with Plane Wave Transmission.

During conventional ultrasound imaging, the need for multiple transmissions for one image and the time of flight for a desired imaging depth limit the frame rate of the system. Using a single plane wave pulse during each transmission followed by parallel receive processing allows for high frame rate imaging. However, image quality is degraded because of the lack of transmit focusing. Beamforming by spatial matched filtering (SMF) is a promising method which focuses ultrasonic energy using spatial filters constructed from the transmit-receive impulse response of the system. Studies by other researchers have shown that SMF beamforming can provide dynamic transmit-receive focusing throughout the field of view. In this paper, we apply SMF beamforming to plane wave transmissions (PWTs) to achieve both dynamic transmit-receive focusing at all imaging depths and high imaging frame rate (>5000 frames per second). We demonstrated the capability of the combined method (PWT + SMF) of achieving two-way focusing mathematically through analysis based on the narrowband Rayleigh-Sommerfeld diffraction theory. Moreover, the broadband performance of PWT + SMF was quantified in terms of lateral resolution and contrast from both computer simulations and experimental data. Results were compared between SMF beamforming and conventional delay-and-sum (DAS) beamforming in both simulations and experiments. At an imaging depth of 40 mm, simulation results showed a 29% lateral resolution improvement and a 160% contrast improvement with PWT + SMF. These improvements were 17% and 48% for experimental data with noise.

Bistatic Multipositional Wave Tomography

A method of bistatic multipositional wave tomography is proposed that is applicable both for the case of radiowave sensing and for the case of ultrasonic sounding. A sensing system is considered in which the transmitter and the receiver are displaced independently in a plane above the investigated object. To acquire threedimensional radio-wave images of scattering objects, the measurement data are processed by the method of spatial matched filtering. The possibility of achieving range resolution even when using monochromatic signals is demonstrated. Results of numerical modeling and experimental studies are presented.

Rotation- and size-invariant object identification system using the liquid crystal on silicon device

We propose a shape discrimination technique using the optical matched spatial filter, which gives an identical result against randomly scattered objects of the same shape but different rotation and scale change. The main idea in this study is to apply optical coordinate transformation, which transforms rotation and scale change including a linear shift into translation, not to the objects themselves but to their Fourier spectra. Thus, rotation and scale change as well as the linear shift can be processed with the same optical matched spatial filter. In addition, we built a two-wavelength system for simultaneous processing of the optical matched spatial filter and optical coordinate transformation. In this system, both Fourier transform and the coordinate transformation were implemented merely by displaying computer-generated holograms (CGH) on the liquid crystal on silicon (LCOS) devices, resulting in a compact lensless system.

Beamforming of sound from two-dimensional arrays using spatial matched filters.

Fully-sampled two-dimensional (2D) arrays can have two-way focusing of the ultrasound beam in both lateral directions leading to high quality, real-time three-dimensional (3D) imaging. However, fully-sampled 2D arrays with very large element counts (>16,000) are difficult to manufacture due to interconnect density and large element electrical impedance. As an alternative, row-column or crossed electrode arrays have been proposed to simplify transducer fabrication and system integration. These types of arrays consist of two one-dimensional arrays oriented perpendicular to each other. Using conventional delay-and-sum beamforming, each array performs one-way focusing in perpendicular lateral directions which yield higher sidelobe and acoustic clutter levels compared to fully-sampled 2D arrays with two-way focusing. In this paper, the use of spatial matched filters to improve focusing of row-column arrays is investigated. On receive, data from each element are first spatial match filtered in the elevation direction. After summation, the data are filtered again in the azimuth direction. Beam widths comparable to one-way focusing are seen in azimuth and beam widths comparable to two-way focusing are achieved in elevation. 3D beam patterns from computer simulation results using a 7.5 MHz 128 × 128 row-column array are shown with comparison to a fully sampled 2D array.

A Novel Combined Beamformer Based on Hypercomplex Processes

The problem of beamforming based on hypercomplex processes is considered for an airborne electromagnetic (EM) vector-sensor array. The quaternion domain facilitates modeling and processing of four-dimensional real signals (or two-dimensional complex signals). Based on the quaternion model of an airborne EM vector-sensor, a quaternion spatial matched filter (QSMF) is presented and its characteristics are analyzed. The quaternion-valued output y(n) of the QSMF consists of two complex components y1(n) and y2(n). The analysis in theory highlights the fact that y2(n) includes only the interference component and noise, but doesn't include the desired signal. By employing y2(n) to cancel the interference component in y1(n), we propose an interference cancellation algorithm (ICA) of the QSMF. In the presence of a strong interference, the ICA can improve the output signal-to-noise ratio (SNR). Based on the interference cancellation structure, we propose two schemes of combined QSMF and complex minimum variance distortionless response (CMVDR) beamformer (one is referred to QSMF-CMVDR and the other is referred to QSMF-DCMVDR) for an airborne EM vector-sensors array. The advantages of the proposed beamformers are that the interference can be canceled by ICA of the QSMF and the additive noise can be reduced by CMVDR beamformer. The output SNR expressions of two combined beamformers that we derive reveal that the output SNR of the QSMF-DCMVDR beamformer is superior to that of a conventional linearly constrained minimum variance (LCMV) beamformer. And in the presence of the coherent (or correlated) interferences, two combined beamformers are not subject to performance degradation. Simulation results are in agreement with our analysis.

Half a century of optics in computing—a personal perspective [Invited

Optical signal processing and computing was triggered by the invention of the laser. Starting practically in 1960, it really took off with the introduction of the spatial-matched filter in 1964. Almost half a century later, research and engineering activity in the field continues unabated but in directions that could not have been anticipated in those early days. This paper presents an overview of the developments in the field, discussing the advantages, disadvantages, and limitations of optics in computing paradigms to indicate where and how optics can be exploited in this area. Initially, optical methods were introduced for processing analog signals. Early attempts to extend optical methods toward digital processing failed because the differences between photons and electrons were not properly appreciated. In the last part of the paper we show that some novel concepts and advanced technology may revitalize also optical processes within the digital computing world. This latter development is demonstrated by digital logic functions implemented on simple electro-optic networks. (My personal perspective on the role of optics in computing is deeply rooted in many years of collaboration with my late friend, H. John Caulfield, and I dedicate this paper to his memory.).

On overloaded vector precoding for single-user MIMO channels

We address the possibility of overloaded vector precoding in single user MIMO channels, i.e. the number of data streams is larger than the minimum of the number of antennas at transmitter and receiver side.We find that the convex vector precoding introduced in [1] allows for overloading while, with a certain probability, keeping the received signal free of interference. We find that the probability that overloading is not possible decays exponentially with the size of the system as long as the number of data streams is less than twice the minimum number of antennas. We give an explicit formula to calculate this probability for any antenna configuration in presence of correlated Rayleigh fading. Although overloading comes with the need for increased transmitted power, we show by means of the replica method that overloading up to 22% yields better spectral and power efficiency than without overload and spatial matched filter processing at the receiver.

Robust finite impulse response beamforming applied to medical ultrasound

We previously described a beamformer architecture that replaces the single apodization weights on each receive channel with channel-unique finite impulse response (FIR) filters. The filter weights are designed to optimize the contrast resolution performance of the imaging system. Although the FIR beamformer offers significant gains in contrast resolution, the beamformer suffers from low sensitivity, and its performance rapidly degrades in the presence of noise. In this paper, a new method is presented to improve the robustness of the FIR beamformer to electronic noise as well as variation or uncertainty in the array response. A method is also described that controls the sidelobe levels of the FIR beamformer's spatial response by applying an arbitrary weighting function in the filter design algorithm. The robust FIR beamformer is analyzed using a generalized cystic resolution metric that quantifies a beamformer's clinical imaging performance as a function of cyst size and channel input SNR. Fundamental performance limits are compared between 2 robust FIR beamformers - the dynamic focus FIR (DF-FIR) beamformer and the group focus FIR (GF-FIR) beamformer - the conventional delay-and-sum (DAS) beamformer, and the spatial-matched filter (SMF) beamformer. Results from this study show that the new DF- and GF-FIR beamformers are more robust to electronic noise compared with the optimal contrast resolution FIR beamformer. Furthermore, the added robustness comes with only a slight loss in cystic resolution. Results from the generalized cystic resolution metric show that a 9-tap robust FIR beamformer outperforms the SMF and DAS beamformer until receive channel input SNR drops below -5 dB, whereas the 9-tap optimal contrast resolution beamformer's performance deteriorates around 50 dB SNR. The effects of moderate phase aberrations, characterized by an a priori root-mean-square strength of 28 ns and an a priori full-width at half-maximum correlation length of 3.6 mm, are investigate- d on the robust FIR beamformers. Full sets of robust FIR beamformer filter weights are constructed using an in silico model scanner and the L14-5/38 mm probe. Using the derived weights, a series of simulated point target and anechoic cyst B-mode images are generated to investigate further the potential increases in contrast resolution when using the robust FIR beamformers. Under the investigated conditions, the 7-tap optimal contrast resolution beamformer and the 7-tap robust beamformer with added SNR constraint increase lesion detectability by 247 and 137% compared with the conventional DAS beamformer, respectively. Finally, experimental phantom and in vivo images are produced using this novel receive architecture. The simulated and experimental images clearly show a reduction in clutter and an increase in contrast resolution compared with the conventionally beamformed images. This novel receive beamformer can be applied to any conventional ultrasound system where the system response is reasonably well characterized.

Generalized cystic resolution: a metric for assessing the fundamental limits on beamformer performance

Existing methods for characterizing the imaging performance of ultrasound systems do not clearly quantify the impact of contrast, spatial resolution, and signal-to-noise ratio (SNR). Although the beamplot, contrast resolution metrics, SNR measurements, ideal observer methods, and contrast-detail analysis provide useful information, it remains difficult to discern how changes in system parameters affect these metrics and clinical imaging performance. In this paper, we present a rigorous methodology for characterizing the pulse-echo imaging performance of arbitrary ultrasound systems. Our metric incorporates the 4-D spatio-temporal system response, which is defined as a function of the individual beamformer channel weights. The metric also incorporates the individual beamformer channel electronic SNR. Whereas earlier performance measures dealt solely with contrast resolution or echo signal-to-noise ratio, our metric combines them so that tradeoffs between these parameters are easily distinguishable. The new metric quantifies an arbitrary system's contrast resolution and SNR performance as a function of cyst size, beamformer channel weights, and beamformer channel SNR. We present a theoretical derivation of the unified performance metric and provide simulation and experimental results highlighting the metric's utility. We compare the fundamental performance limits of 2 beamforming strategies: the dynamic focus finite impulse response (FIR) filter beamformer and the spatial matched filter (SMF) beamformer to the performance of the conventional delay-and-sum (DAS) beamformer. Results from this study show that the SMF beamformer and the FIR beamformer offer significant gains in beamformer SNR and contrast resolution compared with the DAS beamformer, respectively. The metric clearly distinguishes the performance of the SMF beamformer, which enhances system sensitivity, from the FIR beamformer, which optimizes system contrast resolution. Finally, the metric provides one quantitative goal for optimizing a broadband beamformer?s contrast resolution performance.

Influence of multichannel combination, parallel imaging and other reconstruction techniques on MRI noise characteristics

The statistical properties of background noise such as its standard deviation and mean value are frequently used to estimate the original noise level of the acquired data. This requires the knowledge of the statistical intensity distribution of the background signal, that is, the probability density of the occurrence of a certain signal intensity. The influence of many new MRI techniques and, in particular, of various parallel-imaging methods on the noise statistics has neither been rigorously investigated nor experimentally demonstrated yet. In this study, the statistical distribution of background noise was analyzed for MR acquisitions with a single-channel and a 32-channel coil, with sum-of-squares (SoS) and spatial-matched-filter (SMF) data combination, with and without parallel imaging using k-space and image-domain algorithms, with real-part and conventional magnitude reconstruction and with several reconstruction filters. Depending on the imaging technique, the background noise could be described by a Rayleigh distribution, a noncentral chi-distribution or the positive half of a Gaussian distribution. In particular, the noise characteristics of SoS-reconstructed multichannel acquisitions (with k-space-based parallel imaging or without parallel imaging) differ substantially from those with image-domain parallel imaging or SMF combination. These effects must be taken into account if mean values or standard deviations of background noise are employed for data analysis such as determination of local noise levels. Assuming a Rayleigh distribution as in conventional MR images or a noncentral chi-distribution for all multichannel acquisitions is invalid in general and may lead to erroneous estimates of the signal-to-noise ratio or the contrast-to-noise ratio.

SNR Comparisons of Beamforming Strategies

This paper defines the echo signal-to-noise ratio (eSNR) for pulse-echo systems that adapts to the effects of shift-varying impulse responses, spatiotemporal coding, and various beamformers. Measurement techniques using point targets or random scattering media can be interrelated for a broad range of experimental conditions through the eSNR. The eSNR definitions are also illustrated by comparing a spatial matched filter (SMF) beamformer to conventional dynamic receive focusing methods to evaluate performance based on resolution and sensitivity. Closed-form expressions are presented that predict eSNR gains from SMF approaches relative to other beamformers.

Beamforming using spatial matched filtering with annular arrays

A linear array beamforming method for ultrasonic B-mode imaging using spatial matched filtering (SMF) and a rectangular aperture geometry was recently proposed Kim et al., [J. Acoust. Soc. Am. 120, 852-861 (2006)]. This letter extends those results to include circularly symmetric apertures. SMF applied to annular arrays can improve the lateral resolution and echo signal-to-noise ratio as compared with conventional dynamic-receive delay-sum beamforming. At high frequencies, where delay and sum beamforming is problematic, SMF showed greatly improved target contrast over an extended field of view.

Efficient array beam forming by spatial filtering for ultrasound B-mode imaging

This paper proposes an efficient array beam-forming method using spatial matched filtering (SMF) for ultrasonic imaging. In the proposed method, ultrasonic waves are transmitted from an array subaperture with fixed transmit focus as in conventional array imaging. At receive, radio frequency echo signals from each receive channel are passed through a spatial matched filter that is constructed based on the system transmit-receive spatial impulse response. The filtered echo signals are then summed without time delays. The filter concentrates and spatially registers the echo energy from each element so that the pulse-echo impulse response of the summed output is focused with acceptably low side lobes. Analytical beam pattern analysis and simulation results using a linear array show that this spatial filtering method can improve lateral resolution and contrast-to-noise ratio as compared with conventional dynamic receive focusing (DRF) methods. Experimental results with a linear array are consistent but point out the need to address additional practical issues. Spatial filtering is equivalent to synthetic aperture methods that dynamically focus on both transmit and receive throughout the field of view. In one common example of phase aberrations, the SMF method was degraded to a degree comparable to conventional DRF methods.

Intersymbol interference in underwater acoustic communications using time-reversal signal processing

Coherent underwater communication is hampered by the time spread inherent to acoustic propagation in the ocean. Because time-reversal signal processing produces pulse compression, communications has been suggested as a natural application of the technique. Passive versions of time-reversal processing use a receive-only array to do combined temporal and spatial matched filtering. It can be shown, however, that the pulse compression it achieves is not perfect and that an equalizer that relies solely on time-reversal processing will have an error floor caused by uncompensated intersymbol interference (ISI). In the present paper, a physics-based model is developed for the uncompensated ISI in a passive time-reversal equalizer. The model makes use of a normal-mode expansion for the acoustic field. The matched-filtering integral is approximated and the intermediate result interpreted using the waveguide invariant. After combining across the array and sampling, formal statistical averages of the soft demodulation output are calculated. The results show how performance scales with bandwidth, with the number and position of array elements, and with the length of the finite impulse response matched filters. Good agreement is obtained between the predicted scaling and that observed in field experiments.