Fig 5 - uploaded by Damien Garcia
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An appropriate f -number f # can be determined from the directivity of the array elements. The f -number is related to the so-called angle-of-view ( = 2α). The directivity curve and conical sector are those of Fig. 4.
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Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate ultrasound imaging. Its implementation is simple and compatible with real-time applications. In this viewpoint article, we describe the fundamentals of DAS beamforming. The underlying theory and numerical approach are detailed so that users can be aware of its function...
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... s | increases, i.e. when one moves away from the vertex (Fig. 3). For this reason, it is recommended to use the top part only of the hyperbolas during receive beamforming by using an f-number. The receive f-number is defined by the ratio between the depth z s and the width of the receive aperture. It is related to the angle-of-view 2α (defined in Fig. 5) as ...
Context 2
... s | increases, i.e. when one moves away from the vertex (Fig. 3). For this reason, it is recommended to use the top part only of the hyperbolas during receive beamforming by using an f-number. The receive f-number is defined by the ratio between the depth z s and the width of the receive aperture. It is related to the angle-of-view 2α (defined in Fig. 5) as ...
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Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate ultrasound imaging. Its implementation is simple and compatible with real-time applications. In this viewpoint article, we describe the fundamentals of DAS beamforming. The underlying theory and numerical approach are detailed so that users can be aware of its function...
Citations
... By calculating the matrix product of IQ and the sparse tensor M DAS which includes interpolation weights and reception time, the resulting beamformed I/Q data can be obtained as (Perrot et al 2021): ...
... This calculation is referred to as the localization of bubbles. The coordinates of a localized centroid C = (C x , C z ) are given by following equation (Perrot et al 2021): In the bubble detection step of SR-US, the detection thresholds for bubbles vary depending on the imaging method, detection approach, probe type and SNR regarding to the imaging location. To assess the efficiency of PPWs based on different detection threshold I th , the detection rate was studied as a function of the detection threshold in figure 9. Figure 9(a) illustrates the method defined for the symbols indicated in figure 9(b). ...
Objective. Super-resolution ultrasonography offers the advantage of visualization of intricate microvasculature, which is crucial for disease diagnosis. Mapping of microvessels is possible by localizing microbubbles (MBs) that act as contrast agents and tracking their location. However, there are limitations such as the low detectability of MBs and the utilization of a diluted concentration of MBs, leading to the extension of the acquisition time. We aim to enhance the detectability of MBs to reduce the acquisition time of acoustic data necessary for mapping the microvessels. Approach. We propose utilizing phase patterned waves (PPWs) characterized by spatially patterned phase distributions in the incident beam to achieve this. In contrast to conventional ultrasound irradiation methods, this irradiation method alters bubble interactions, enhancing the oscillation response of MBs and generating more significant scattered waves from specific MBs. This enhances the detectability of MBs, thereby enabling the detection of MBs that were undetectable by the conventional method. The objective is to maximize the overall detection of bubbles by utilizing ultrasound imaging with additional PPWs, including the conventional method. In this paper, we apply PPWs to ultrasound imaging simulations considering bubble–bubble interactions to elucidate the characteristics of PPWs and demonstrate their efficacy by employing PPWs on MBs fixed in a phantom by the experiment. Main results. By utilizing two types of PPWs in addition to the conventional ultrasound irradiation method, we confirmed the detection of up to 93.3% more MBs compared to those detected using the conventional method alone. Significance. Ultrasound imaging using additional PPWs made it possible to increase the number of detected MBs, which is expected to improve the efficiency of bubble detection.
... In our application, we circumvent this issue through a novel PyTorch implementation of the derivative of the DAS beamforming operator B. Because the beamformed image I is linear as a function of the multistatic data U (Perrot et al 2021), the analytic derivative needed for backpropagation is simply its adjoint operator. We provide PyTorch the DAS adjoint for arbitrary data, which eliminates the additional cost and memory overhead. ...
... We do not directly construct and transpose the DAS beamforming matrix, as it is impractically large for reasonably sized multistatic data, even under a sparse representation (Perrot et al 2021). Instead, we apply this adjoint matrix-free, recognizing that B can be described as a sum of linear interpolations, or ...
Objective. The transmit encoding model for synthetic aperture imaging is a robust and flexible framework for understanding the effects of acoustic transmission on ultrasound image reconstruction. Our objective is to use machine learning (ML) to construct scanning sequences, parameterized by time delays and apodization weights, that produce high-quality B-mode images. Approach. We use a custom ML model in PyTorch with simulated RF data from Field II to probe the space of possible encoding sequences for those that minimize a loss function that describes image quality. This approach is made computationally feasible by a novel formulation of the derivative for delay-and-sum beamforming. Main results. When trained for a specified experimental setting (imaging domain, hardware restrictions, etc), our ML model produces optimized encoding sequences that, when deployed in the REFoCUS imaging framework, improve a number of standard quality metrics over conventional sequences including resolution, field of view, and contrast. We demonstrate these results experimentally on both wire targets and a tissue-mimicking phantom. Significance. This work demonstrates that the set of commonly used encoding schemes represent only a narrow subset of those available. Additionally, it demonstrates the value for ML tasks in synthetic transmit aperture imaging to consider the beamformer within the model, instead of purely as a post-processing step.
... Traditional multi-channel speech enhancement primarily relies on beamforming algorithms, which design filters based on the target signal and noise collected from different directions by the array. Common beamformers include delay-and-sum [2], minimum variance distortionless response (MVDR) [3], lin-B Dongmei Li lidmei@tsinghua.edu.cn Zhengdong Cao czd21@mails.tsinghua.edu.cn 1 Department of Electronic Engineering, Tsinghua University, Beijing 100084, China ear constraint minimum variance (LCMV) [4], generalized sidelobe canceler (GSC) [5], and so on. ...
In this paper, a multi-channel speech enhancement structure combining beamformers and lightweight neural networks is proposed. By using a first-order differential beamformer to improve the signal-to-noise ratio of the target speech, the burden on the subsequent neural network is reduced, thus lowering the complexity of the required neural network. A two-stage gated recurrent neural network is employed, where the first stage recurrent neural network processes the channel characteristics of the speech and the second handles the frequency domain features of the speech. The frequency band division combined with convolution is used to further compress the network scale. With suitable loss function, the speech enhancement performance of the model is further improved. The proposed model structure is trained, evaluated, and validated using simulated multi-channel microphone array datasets generated from the public TIMIT dataset. The results demonstrate that our model achieves good multi-channel speech enhancement performance with relatively small parameter and computational requirements when compared to popular existing approaches.
... For the beamforming process, we use the MUST [37] toolbox after employing the amplitude modulation (AM) technique and a virtual point source formulation as described by Garcia et. al. [38]. ...
Contrast-enhanced ultrasound (CEUS) presents distinct advantages in diagnostic echography. Utilizing microbubbles (MBs) as conventional contrast agents enhances vascular visualization and organ perfusion, facilitating real-time, non-invasive procedures. There is a current tendency to replace the traditional polydisperse MBs by novel monodisperse formulations in an attempt to optimize contrast enhancement and guarantee consistent behavior and reliable imaging outcomes. This study investigates the contrast enhancement achieved by monodisperse MBs of different sizes, and their influence on nonlinear imaging artifacts observed in traditional CEUS. To explore the differences between monodisperse and polydisperse populations without excessive experimentation, numerical simulations are employed for delivering precise, objective and expeditious results. The Iterative Nonlinear Contrast Source (INCS) method has previously demonstrated its efficacy in simulating ultrasound propagation in large populations in which each bubble has individual properties and several orders of multiple scattering are significant. Our findings in CEUS imaging indicate that scattering from resonant monodisperse microbubbles is 11.8 dB stronger than scattering from the polydisperse population. Furthermore, the amplitude of nonlinear imaging artifacts downstream of the monodisperse population is 19.4 dB stronger compared to polydisperse suspension. Investigating the impact of multiple scattering on polydisperse populations compared to various monodisperse suspensions reveals that monodisperse MBs are more effective contrast agents, especially when on resonance. Despite the strong signal to noise ratio of monodisperse populations, the imaging artifacts due to nonlinear wave propagation are also enhanced, resulting in more missclassification of MBs as tissue.
... The field of view of each element was considered 30° and therefore, the weight of the grids located at angles above 30° was 0 [67]. Note that this is an alternative approach of using a dynamic F-number (F#) in the beamformer where the opening angle is related to the F# by # = 1/(2 * tan( )), where FOV is the field of view [68]. For beamforming, a grid size of 18 µm and 46 µm was used in the axial and lateral directions, respectively. ...
Arteriosclerosis results from lipid buildup in artery walls, leading to plaque formation, and is a leading cause of death. Plaque rupture can cause blood clots that might lead to a stroke. Distinguishing plaque types is a challenge, but ultrasound elastography can help by assessing plaque composition based on strain values. Since the artery has a circular structure, an accurate axial and lateral displacement strategy is needed to derive the radial and circumferential strains. A high precision lateral displacement is challenging due to the lack of phase information in the lateral direction of the beamformed RF data. Previously, our group has developed a compounding technique in which the lateral displacement is estimated using tri-angulation of the axial displacement estimated from transmitting and beamforming ultrasound beams at ±20°. However, transmitting with a single plane wave will reduce signal-to-noise and contrast-to-noise ratio as well as lateral resolution. In this paper, we combine our displacement compounding with coherent compounding. Instead of transmitting a single plane wave, multiple plane waves are transmitted at certain angles centered on the angle of the beamforming grids, and then the backscattered wavefronts are beamformed and coherently compounded on the center of the transmit beams (-20°, +20° and 0°). The numerical investigation using the GE9LD probe (f
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= 5.32 MHz, pitch = 230 μm, width = 43.9 mm) led us to 19 plane waves spanning angles within -10° to 10° (with respect to center of the transmit beams); resulting in a total of 57 plane wave transmit (for 3 beamforming grids at 0° and ±20°). FIELD II simulations of a cylindrically-shaped phantom (mimicking the carotid artery) at a signal-to-noise ratio ≥ 20 dB shows that the proposed method decreases the root-mean-square-error of the lateral displacement and strain estimations by 40% and 45% compared to the previous method, respectively. The results of our experiments with a carotid artery phantom (made out of 10% PVA) show that the proposed method provides strain images with a higher quality and more in agreement with the theory, with 26% lower standard deviation, specially at the peak systolic phase. The proposed method paves the path toward improved quality in vivo 2D strain imaging using our displacement compounding technique and translating it to 3D with a row-column array.
... ULSE-ECHO ultrasound imaging relies on time-of-flight calculations based on the speed-of-sound (SoS) to form ultrasound images. Typically, for image formation, the SoS inside the human body is assumed to be a constant 1540 m/s [1]. While this assumption is sufficient for forming images with adequate quality, it neglects to account for the varying SoS of different types of tissue (e.g., muscle versus fat) in the human body [2], [3]. ...
... Steered plane wave acquisitions were then beamformed at a lower SoS [ Fig. 1 In contrast, the PSF spreading was apparent in SoS mismatch scenarios. The loss of resolution in scenarios with SoS mismatch was caused by summation along the incorrect hyperbolas during DAS beamforming [1]. For scenarios with SoS mismatch, not only was the resolution worsened, but also the PSFs of the point targets were positionally offset for different steering angles. ...
... To efficiently beamform the entire data tensor, we applied sparse matrix beamforming (SMB) for GPU acceleration. SMB has demonstrated high efficiency previously for high-intensity focused ultrasound monitoring and passive acoustic mapping but has also proven to be an effective means of acceleration for DAS beamforming [1], [40], [41]. SMB enabled simple conversion of our DAS beamforming algorithm (Sec. ...
Speed-of-sound (SoS) is an intrinsic acoustic property of human tissues and has been regarded as a potential biomarker of tissue health. To foster the clinical use of this emerging biomarker in medical diagnostics, it is important for SoS estimates to be derived and displayed in real-time. Here, we demonstrate that concurrent global SoS estimation and B-mode imaging can be achieved live on a portable ultrasound scanner. Our innovation is hinged upon the design of a novel pulse-echo SoS estimation framework that is based on steered plane wave imaging. It has accounted for the effects of refraction and imaging depth when the medium SoS differs from the nominal value of 1540 m/s that is conventionally used in medical imaging. The accuracy of our SoS estimation framework was comparatively analyzed with through-transmit time-of-flight measurements
in vitro
on 15 custom agar phantoms with different SoS values (1508 to 1682 m/s) and
in vivo
on human calf muscles (N = 9; SoS range: 1560 to 1586 m/s). Our SoS estimation framework has a mean signed difference of, respectively, -0.6±2.3 m/s
in vitro
and -2.2±11.2 m/s
in vivo
relative to the reference measurements. Additionally, our real-time system prototype has yielded simultaneous SoS estimates and B-mode imaging at an average frame rate of 18.1 fps. Overall, by realizing real-time tissue SoS estimation with B-mode imaging, our innovation can foster the use of tissue SoS as a biomarker in medical ultrasound diagnostics.
... Due to acoustic reciprocity, the response remains unchanged when the source and receiver are swapped. Expression (17) can therefore provide the pressure received by the m th sub-element from a scatterer s, after accounting for its reflection coefficient R s : ...
... The superscript "se" refers to "sub-element". Inserting (17) in (19), it follows that: ...
... A total of 16 plane waves were transmitted with tilt angles linearly spaced between − 7 and +7 • in both elevational and azimuthal directions. During beamforming, the f-number was determined automatically based on a directivity criterion, as explained in [17,18]. A volume B-mode image was created after compounding the 16 beamformed I/Q volumes. ...
... Such phantoms provide an invaluable approach to objective, quantitative evaluation of image quality characteristics. The image was obtained using the 128-linear array on so-called plane wave compounding (of nine plane wave transmissions) 33 in combination with delay-and-sum beamforming in reception 34 [20,30] mm that are typically used to determine the axial/lateral resolution are also clearly visible and well separated. The hyperechoic region at [−20, 30] mm is clearly visible, as is the 10 kPa elasticity target at [5,15] mm. ...
With the huge progress in micro-electronics and artificial intelligence, the ultrasound probe has become the bottleneck in further adoption of ultrasound beyond the clinical setting (e.g. home and monitoring applications). Today, ultrasound transducers have a small aperture, are bulky, contain lead and are expensive to fabricate. Furthermore, they are rigid, which limits their integration into flexible skin patches. New ways to fabricate flexible ultrasound patches have therefore attracted much attention recently. First prototypes typically use the same lead-containing piezo-electric materials, and are made using micro-assembly of rigid active components on plastic or rubber-like substrates. We present an ultrasound transducer-on-foil technology based on thermal embossing of a piezoelectric polymer. High-quality two-dimensional ultrasound images of a tissue mimicking phantom are obtained. Mechanical flexibility and effective area scalability of the transducer are demonstrated by functional integration into an endoscope probe with a small radius of 3 mm and a large area (91.2×14 mm ² ) non-invasive blood pressure sensor.
... Traditional multi-channel speech enhancement primarily relies on beamforming algorithms, which design őlters based on the target signal and noise collected from different directions by the array. Common beamformers include delay-and-sum [2], minimum variance distortionless response (MVDR) [3], linear constraint minimum variance (LCMV) [4], generalized sidelobe canceler (GSC) [5], and so on. The beamformer of a microphone array can improve the signal-to-noise ratio to a certain extent, but the speech enhancement effect of purely using beamforming algorithms is limited. ...
In this paper, a multi-channel speech enhancement structure combining beamformers and lightweightneural networks is proposed. By using a first-order differential beamformer to improve the signalto-noise ratio of the target speech, the burden on the subsequent neural network is reduced, thuslowering the complexity of the required neural network. A two-stage gated recurrent neural networkis employed, where the first stage recurrent neural network processes the channel characteristics ofthe speech and the second handles the frequency domain features of the speech. The frequency banddivision combined with convolution is used to further compress the network scale. With suitable lossfunction, the speech enhancement performance of the model is further improved.The proposed modelstructure is trained, evaluated, and validated using simulated multi-channel microphone array datasetsgenerated from the public TIMIT dataset. The results demonstrate that our model achieves goodmulti-channel speech enhancement performance with relatively small parameter and computationalrequirements when compared to popular existing approaches.
... Volume beamforming was realized in agreement with delay and sum beamforming [30]. We adjusted the forward delay in agreement with the kind of waves used. ...
... The receive distance DRX was common to the different insonification sequences and corresponded to the spherical wavefront generated by the point scatterer as described in Perrot et al. [30]. ...
Transcranial ultrasound plays a limited role in neuroradiology due to its lack of resolution, planar imaging, and user-dependency. By breaching the diffraction limit using injected microbubbles, volumetric ultrasound localization microscopy (ULM) could help alleviate those issues. However, performing 3D ultrasound imaging at a high frame rate with sufficient signal-to-noise ratio to track individual microbubbles through the skull remains a challenge, especially with a portable scanner. In this study, we describe a ULM sequence suitable for volumetric transcranial imaging exploiting cylindrical emissions on multiplexed matrix probes, through simulations, hydrophone measurements, and flow phantoms. This geometry leads to a doubling of the peak acoustic pressure, up to 400 kPa, with respect to spherical emission and improved volume rate, up to 180 Hz. Cylindrical emissions also improve ULM saturation rate by 60% through a skull phantom. The assessment of microbubble velocity was also improved from 33% error in the average flow measured with spherical waves to a 5% error with cylindrical waves. Conversely, we demonstrate the detrimental impacts of cylindrical waves toward the field of view and isotropic sensitivity. Nevertheless, due to its enhanced signal-to-noise ratio and 3D nature, such a cylindrical volumetric sequence could be beneficial for ULM as a diagnostic tool in humans, especially when portability is a necessity.
