Synthetic Transmit Aperture Imaging Research Articles

Optimization of array encoding for ultrasound imaging

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.

Deep Null Space Learning Improves Dataset Recovery for High Frame Rate Synthetic Transmit Aperture Imaging.

Synthetic transmit aperture (STA) imaging benefits from the two-way dynamic focusing to achieve optimal lateral resolution and contrast resolution in the full field of view, at the cost of low frame rate (FR) and low signal-to-noise ratio (SNR). In our previous studies, compressed sensing based synthetic transmit aperture (CS-STA) and minimal l2-norm least squares (LS-STA) methods were proposed to recover the complete STA dataset from fewer Hadamard-encoded plane wave (PW) transmissions. Results demonstrated that, compared with STA imaging, CS/LS-STA can maintain the high resolution of STA in the full field of view and improve the contrast in the deep region with increased FR. However, these methods would introduce errors to the recovered STA datasets and subsequently produce severe artifacts to the beamformed images, especially in the shallow region. Recently, we discovered that the theoretical explanation for the error introduced in the LS-STA-based recovery is that the LS-STA method neglects the null space component of the real STA dataset. To deal with this problem, we propose to train a convolutional neural network under the null space learning framework (CNN-Null) to estimate the missing null space component) for high-accuracy recovery of the STA dataset from fewer Hadamard-encoded PW transmissions. The mapping between the low-quality STA dataset (i.e., the range space component of the real STA dataset recovered using the LS-STA method) and the missing null space component of the real STA dataset was learned by the network with the high-quality STA dataset (obtained using full Hadamard-encoded STA imaging, HE-STA) as training labels. The performance of the proposed CNN-Null method was compared with the baseline LS-STA, conventional STA, and HE-STA methods, in terms of visual quality, normalized root-mean-square error (NRMSE), generalized contrast-to-noise ratio (gCNR), and lateral full width at half maximum (FWHM). The results demonstrate that the proposed method can greatly improve the recovery accuracy of the STA datasets (lower NRMSE) and therefore effectively suppress the artifacts presented in the images (especially in the shallow region) obtained using the LS-STA method (with a gCNR improvement of 0.4 in the cross-sectional carotid artery images). In addition, the proposed method can maintain the high lateral resolution of STA with fewer (as low as 16) PW transmissions, as LS-STA does.

Hadamard-Encoded Synthetic Transmit Aperture Imaging for Improved Lateral Motion Estimation in Ultrasound Elastography.

Lateral motion estimation has been a challenge in ultrasound elastography mainly due to the low resolution, low sampling frequency, and lack of phase information in the lateral direction. Synthetic transmit aperture (STA) can achieve high resolution due to two-way focusing and can beamform high-density image lines for improved lateral motion estimation with the disadvantages of low signal-to-noise ratio (SNR) and limited penetration depth. In this study, Hadamard-encoded STA (Hadamard-STA) is proposed for the improvement of lateral motion estimation in elastography, and it is compared with STA and conventional focused wave (CFW) imaging. Simulations, phantom, and in vivo experiments were conducted to make the comparison. The normalized root mean square error (NRMSE) and the contrast-to-noise ratio (CNR) were calculated as the evaluation criteria in the simulations. The results show that, at a noise level of -10 dB and an applied strain of -1% (compression), Hadamard-STA decreases the NRMSEs of lateral displacements by 46.92% and 35.35%, decreases the NRMSEs of lateral strains by 52.34% and 39.75%, and increases the CNRs by 9.70 and 9.75 dB compared with STA and CFW, respectively. In the phantom experiments performed on a heterogeneous tissue-mimicking phantom, the sum of squared differences (SSD) between the reference and the motion-compensated RF data, and the CNR were calculated as the evaluation criteria. At an applied strain of -1.80%, Hadamard-STA is found to decrease the SSDs by 20.91% and 30.99% and increase the CNRs by 14.15 and 24.66 dB compared with STA and CFW, respectively. In the experiments performed on a breast phantom, Hadamard-STA achieves better visualization of the breast inclusion with a clearer boundary between the inclusion and the background than STA and CFW. The in vivo experiments were performed on a patient with a breast tumor, and the tumor could also be better visualized with a more homogeneous background in the strain image obtained by Hadamard-STA than by STA and CFW. These results demonstrate that Hadamard-STA achieves a substantial improvement in lateral motion estimation and maybe a competitive method for quasi-static elastography.

Acceleration of reconstruction for compressed sensing based synthetic transmit aperture imaging by using in-phase/quadrature data

Compressed sensing-based synthetic transmit aperture (CS-STA) was previously proposed to recover the full radio-frequency (RF) channel dataset of synthetic transmit aperture (STA) from that of a smaller number of randomly apodized plane wave (PW) transmissions. In this way, the imaging frame rate (FR) and contrast are improved with maintained spatial resolution, compared with those of STA. Because CS-STA reconstruction is repeated for all receive elements and RF samples (with a high sampling frequency), the recovery of STA dataset in RF domain is time-consuming. In the meantime, a large amount of RF data needs to be transferred and stored, resulting in an increase of system complexity and required memory space. In this study, CS-STA is extended to in-phase/quadrature (IQ) domain (with lower sampling frequency) for the recovery of baseband STA IQ dataset to accelerate the CS-STA reconstruction by reducing the amount of data to be processed. More importantly, CS-STA reconstruction using IQ data is of practical importance, as clinical ultrasound systems typically record baseband IQ signal instead of RF signal. Simulations, phantom and in vivo experiments verify the feasibility of CS-STA in IQ domain for the recovery of STA dataset. More specifically, CS-STA using IQ data achieves similar image quality and appreciably improves reconstruction speed (by ∼3 times) compared with that using RF data. These findings demonstrate that IQ-domain CS-STA is capable of relieving the computational and storage burdens, which may facilitate the implementation of CS-STA in practical ultrasound systems.

ApodNet: Learning for High Frame Rate Synthetic Transmit Aperture Ultrasound Imaging.

Two-way dynamic focusing in synthetic transmit aperture (STA) beamforming can benefit high-quality ultrasound imaging with higher lateral spatial resolution and contrast resolution. However, STA requires the complete dataset for beamforming in a relatively low frame rate and transmit power. This paper proposes a deep-learning architecture to achieve high frame rate STA imaging with two-way dynamic focusing. The network consists of an encoder and a joint decoder. The encoder trains a set of binary weights as the apodizations of the high-frame-rate plane wave transmissions. In this respect, we term our network ApodNet. The decoder can recover the complete dataset from the acquired channel data to achieve dynamic transmit focusing. We evaluate the proposed method by simulations at different levels of noise and in-vivo experiments on the human biceps brachii and common carotid artery. The experimental results demonstrate that ApodNet provides a promising strategy for high frame rate STA imaging, obtaining comparable lateral resolution and contrast resolution with four-times higher frame rate than conventional STA imaging in the in-vivo experiments. Particularly, ApodNet improves contrast resolution of the hypoechoic targets with much shorter computational time when compared with other high-frame-rate methods in both simulations and in-vivo experiments.

3-D Large-Pitch Synthetic Transmit Aperture Imaging With a Reduced Number of Measurement Channels: A Feasibility Study.

A 3-D synthetic transmit aperture ultrasound imaging system with a fully addressed array usually leads to high hardware complexity and cost since each element in the array is individually controlled. To reduce the hardware complexity, we had presented the large-pitch synthetic transmit aperture (LPSTA) ultrasound imaging for 2-D imaging using a 1-D phased array to reduce the number of measurement channels M (the product of number of transmissions, [Formula: see text], and the number of receiving channels in each transmission, [Formula: see text]). In this article, we extend this method to a 2-D matrix array for 3-D imaging. We present both numerical simulations and experimental measurements. We combined L × L adjacent elements into transmission subapertures (SAP) and K × K adjacent elements into receive SAPs in synthetic transmit aperture (STA) imaging. In the image reconstruction, we conducted the first attempt to apply and integrate Gaussian-approximated spatial response function (G-SRF) with delay and sum (DAS) to improve the image contrast, especially for the near-field targets. The imaging performance obtained from G-SRF was also evaluated numerically and compared with the previously presented frequency-domain SRF (Freq-domain SRF). The 3-D large-pitch synthetic transmit aperture (3-D-LPSTA) with G-SRF can provide a computationally efficient solution compared with the standard 3-D-STA method. With approximately 1900-fold reduction in the number of measurement channels, 3-D-LPSTA can provide image contrast comparable with the standard 3-D-STA with a full array and significantly better than using a periodically sparse array with similar complexity. In addition to reducing the system complexity, the 3-D-LPSTA achieves 700-fold reduction in computational complexity and 523-fold reduction in data storage. Finally, we evaluated and implemented the G-SRF using phantom data, which were consistent with the simulation results showing that the G-SRF can improve the image contrast. The results demonstrate that the proposed 3-D-LPSTA shows the great potential for designing an inexpensive ultrasound system to ensure the real-time 3-D clinical ultrasound imaging using large arrays. The limits of the proposed method were also discussed.

Towards practical implementation of the compressed sensing framework for multi-element synthetic transmit aperture imaging

Compressed sensing (CS) has been adapted to synthetic aperture (SA) ultrasound imaging to improve the frame-rate of the system. Recently, we proposed a novel CS framework using Gaussian under-sampling to reduce the number of receive elements in multi-element synthetic transmit aperture (MSTA) imaging. However, that framework requires different receive elements to be chosen randomly for each transmission, which may add to practical implementation challenges. Modifying the scheme to employ the same set of receive elements for all transmissions of MSTA leads to degradation of the recovered image quality. Therefore, this work proposes a novel sampling scheme based on a genetic algorithm (GA), which optimally chooses the receive element positions once and uses it for all the transmission of MSTA. The CS performance using GA sampling schemes is evaluated against the previously proposed CS framework on in-vitro and in-vivo datasets. The obtained results suggest that not only does the GA-based approach allows the use of the same set of sparse receive elements for each transmit, but also leads to the lowest CS recovery error (NRMSE) and 14% overall improvement in image contrast, in comparison to the previously-proposed Gaussian sampling scheme. Thus, using the CS framework along with GA, can potentially reduce the complexity in implementation of CS-framework to MSTA based systems.

Laser-induced synthetic aperture ultrasound imaging

This work concerns the development and testing of a setup that uses laser-induced ultrasound sources to achieve synthetic transmit aperture ultrasound imaging. The sources are created by sequentially firing 32 contiguous multi-mode optical fibers to illuminate an optically absorbing film with nanosecond-pulsed laser light. Ultrasound is generated by the photoacoustic effect and insonifies the sample under investigation. Ultrasound that has interacted with the sample is detected in reflection mode using a conventional ultrasound transducer array. We present a custom-developed optical fiber multiplexing setup that enables sequential firing of the optical fiber array and characterize the acoustic fields produced by the laser-induced approach using hydrophone measurements. The integrated setup is used to make images of wire phantoms. Following this, images are taken of a breast-mimicking phantom as well as the wrist of one of the authors. Imaging results from the new approach and from conventional ultrasound imaging are compared. The lateral and axial point-spread function values show broad agreement between the two approaches, whereas the phantom and in vivo images exhibit some differences in contrast values. This work is, to our knowledge, the first instance of laser-induced ultrasound synthetic transmit aperture imaging using a clinical ultrasound array.

Compressed Sensing Approach for Reducing the Number of Receive Elements in Synthetic Transmit Aperture Imaging.

Recently, researchers have shown an increased interest in ultrasound imaging methods alternate to conventional focused beamforming (CFB). One such approach is based on the synthetic aperture (SA) scheme; more popular are the ones based on synthetic transmit aperture (STA) schemes with a single-element transmit or multielement STA (MSTA). However, one of the main challenges in translating such methods to low-cost ultrasound systems is the tradeoffs among image quality, frame rate, and complexity of the system. These schemes use all the transducer elements during receive, which dictates a corresponding number of parallel receive channels, thus increasing the complexity of the system. A considerable amount of literature has been published on compressed sensing (CS) for SA imaging. Such studies are aimed at reducing the number of transmissions in SA but still recover images of acceptable quality at high frame rate and fail to address the complexity due to full-aperture receive. In this work, we adopt a CS framework to MSTA, with a motivation to reduce the number of receive elements and data. The CS recovery performance was assessed for the simulation data, tissue-mimicking phantom data, and an example in vivo biceps data. It was found that in spite of using 50% receive elements and overall using only 12.5% of the data, the images recovered using CS were comparable to those of reference full-aperture case in terms of estimated lateral resolution, contrast-to-noise ratio, and structural similarity indices. Thus, the proposed CS framework provides some fresh insights into translating the MSTA imaging method to affordable ultrasound scanners.

Large-Pitch Synthetic Transmit Aperture Imaging: A Feasibility Study.

A 3-D or large-aperture 2-D synthetic transmit aperture (STA) ultrasound imaging system with a fully sampled array usually leads to high hardware complexity and cost since each element in the array is individually controlled. To reduce the hardware complexity, we propose a large-pitch method for STA (LPSTA) imaging integrated with a spatial response function (SRF) in the image reconstruction to improve image quality. To achieve this, we decreased the total number of measurement channels M (the product of the number of transmissions IT and the number of the receive channels in each transmission IR ). We combined L adjacent elements in transmission and K adjacent elements in receive into subapertures (SAPs), where L and K were coprime (no common factors) integers to suppress the grating lobes. We denoted it as an ( N/L, N /K ) system, where N is the number of transducer elements. In this article, first, we derived the beam pattern of the LPSTA using a far-field approximation. We demonstrated that the coprime selection and SRF can significantly reduce the grating lobes level (GLL) by using a beam pattern analysis. We also found that the LPSTA can have a similar beam pattern as that of a full array when the target is located along the steering direction. Second, the imaging performance of LPSTA was evaluated and validated with Field II simulations and experiments. The simulation results demonstrated that the proposed LPSTA with ( N /3, N /5) can achieve on average ~25% improvement in lateral resolution, ~24.6% and ~42.3% improvement in contrast-to-noise ratio (CNR) and contrast ratio (CR), respectively, over B-mode with a large-pitch receiver with ( N , N /5). LPSTA achieved comparable image contrast to the standard STA with the full array ( N , N ) at the cost of a reduced field of view. The experiment results were consistent with the simulation results. Finally, in addition to reducing the system (hardware) complexity, the LPSTA was more computationally efficient than the standard STA with a full array. The proposed method may help in realizing clinical applications of real-time 2-D or 3-D ultrasound imaging using large arrays.

Fast Super-Resolution Ultrasound Imaging With Compressed Sensing Reconstruction Method and Single Plane Wave Transmission

Super-resolution ultrasound (SR-US) imaging technique breaks the diffraction limit and can image microvascular structure. However, the temporal resolution of SR-US is limited because a long data acquisition time is required to accumulate enough microbubbles. To overcome this limitation, in this paper, we proposed a new SR-US method based on compressed sensing (CS), which is used to identify the highly overlapped microbubbles in each frame. To further speed up the data acquisition of SR-US, here, U.S. data was generated by single plane wave (SPW) transmission. To evaluate the performance of the proposed technique (CS reconstruction method combined with SPW transmission, termed as CSRM-SPW), a series of numerical simulation was performed. Especially, considering that SPW has a relatively low spatial resolution, it may affect the obtained SR-US imaging performance. We compare the effect of synthetic transmit aperture (STA) and SPW on SR-US. The results indicate the overlapped microbubbles can be identified by the CSRM method when compared with the traditional localization method (e.g., Gaussian fitting method). In addition, whatever STA or SPW images are used as the input data of CS reconstruction, the localization accuracy of SR-US obtained by the CSRM method is similar. Further, by using the CSRM combined with SPW technique, the vascular network can be accurately resolved, even if the high-density microbubbles existed in each frame. As a result, the proposed CSRM-SPW technique is suitable for fast SR-US imaging.

Signal Eigenvalue Factor for Synthetic Transmit Aperture Ultrasound Imaging

Synthetic transmit aperture (STA) ultrasound imaging that obtain bi-directional focusing can create a high-resolution image. Delay-and-sum (DAS) approach is performed in both transmit and receive modes, which leads to low contrast and high sidelobe. Adaptive weighting technology is effective in improving image quality. This paper proposes a new adaptive weighting factor namely signal eigenvalue factor (SEF) for STA imaging. SEF performs eigenvalue decomposition on transmitting aperture, and then it uses the larger eigenvalues as the weighting factor to carry out the adaptive imaging. For comparison, conventional coherence factor (CF) method is also presented. Simulation and experimental results show that SEF method can get higher resolution than CF and DAS. In addition, the contrast radio and contrast-to-noise radio can be enhanced, especially for massive cyst.

Specular Beamforming.

Acoustically hard objects, such as bones, needles, or catheters, are poorly visualized in conventional ultrasound images. These objects behave like acoustic mirrors and reflect sound in specific directions. Soft tissue and diffusive reflectors scatter sound in a broad range of directions. Conventional delay-and-sum beamforming is based on the assumption of a purely scattering domain with relatively weak reflectivity. We present an adaptive beamforming technique that takes into account the physics of specular reflection. Patterns predicted by the law of reflection are detected across the pool of received data and used to enhance the visualization of specular energy. This technique can be applied to any synthetic imaging sequence. Here, it is applied to synthetic transmit aperture imaging. In vitro experiments show a clear improvement in target visibility and an increase of 30 to 60 dB in signal-to-noise ratio.

Ultrafast Synthetic Transmit Aperture Imaging Using Hadamard-Encoded Virtual Sources With Overlapping Sub-Apertures.

The development of ultrafast ultrasound imaging offers great opportunities to improve imaging technologies, such as shear wave elastography and ultrafast Doppler imaging. In ultrafast imaging, there are tradeoffs among image signal-to-noise ratio (SNR), resolution, and post-compounded frame rate. Various approaches have been proposed to solve this tradeoff, such as multiplane wave imaging or the attempts of implementing synthetic transmit aperture imaging. In this paper, we propose an ultrafast synthetic transmit aperture (USTA) imaging technique using Hadamard-encoded virtual sources with overlapping sub-apertures to enhance both image SNR and resolution without sacrificing frame rate. This method includes three steps: 1) create virtual sources using sub-apertures; 2) encode virtual sources using Hadamard matrix; and 3) add short time intervals (a few microseconds) between transmissions of different virtual sources to allow overlapping sub-apertures. The USTA was tested experimentally with a point target, a B-mode phantom, and in vivo human kidney micro-vessel imaging. Compared with standard coherent diverging wave compounding with the same frame rate, improvements on image SNR, lateral resolution (+33%, with B-mode phantom imaging), and contrast ratio (+3.8 dB, with in vivo human kidney micro-vessel imaging) have been achieved. The f-number of virtual sources, the number of virtual sources used, and the number of elements used in each sub-aperture can be flexibly adjusted to enhance resolution and SNR. This allows very flexible optimization of USTA for different applications.

Compressed Sensing Based Synthetic Transmit Aperture Imaging: Validation in a Convex Array Configuration.

According to the linear acoustic theory, the channel data of a plane wave emitted by a linear array is a linear combination of the full data set of synthetic transmit aperture (STA). Combining this relationship with compressed sensing (CS), a novel CS based ultrasound beamforming strategy, named compressed sensing based synthetic transmit aperture (CS-STA), was previously proposed to increase the frame rate of ultrasound imaging without sacrificing the image quality for a linear array. In this paper, assuming linear transfer function of a pulse-echo ultrasound system, we derived and applied the theory of CS-STA for a slightly curved array and validated CS-STA in a convex array configuration. Computer simulations demonstrated that, in the convex array configuration, the normalized root-mean-square error between the beamformed radio-frequency data of CS-STA and STA was smaller than 1% while CS-STA achieved four-fold higher frame rate than STA. In addition, CS-STA was capable of achieving good image quality at depths over 100 mm. It was validated in phantom experiments by comparing CS-STA with STA, multielement synthetic transmit aperture (ME-STA), and the conventional focused method (focal depth = 110 mm). The experimental results showed that STA and CS-STA performed better than ME-STA and the focused method at small depths. At the depth of 110 mm, CS-STA, ME-STA, and the focused methods improved the contrast and contrast-to-noise ratio of STA. The improvements in CS-STA are higher than those in ME-STA but lower than those in the focused mode. These results can also be observed qualitatively in the in vivo experiments on the liver of a healthy male volunteer. The CS-STA method is thus proved to increase the frame rate and achieve high image quality at full depth in the convex array configuration.

Effects of line fiducial parameters and beamforming on ultrasound calibration.

Ultrasound (US)-guided interventions are often enhanced via integration with an augmented reality environment, a necessary component of which is US calibration. Calibration requires the segmentation of fiducials, i.e., a phantom, in US images. Fiducial localization error (FLE) can decrease US calibration accuracy, which fundamentally affects the total accuracy of the interventional guidance system. Here, we investigate the effects of US image reconstruction techniques as well as phantom material and geometry on US calibration. It was shown that the FLE was reduced by 29% with synthetic transmit aperture imaging compared with conventional B-mode imaging in a Z-bar calibration, resulting in a 10% reduction of calibration error. In addition, an evaluation of a variety of calibration phantoms with different geometrical and material properties was performed. The phantoms included braided wire, plastic straws, and polyvinyl alcohol cryogel tubes with different diameters. It was shown that these properties have a significant effect on calibration error, which is a variable based on US beamforming techniques. These results would have important implications for calibration procedures and their feasibility in the context of image-guided procedures.

Ultrasonic imaging of defects in coarse-grained steels with the decomposition of the time reversal operator.

In the present work, the Synthetic Transmit Aperture (STA) imaging is combined with the Decomposition of the Time Reversal Operator (DORT) method to image a coarse grained austenitic-ferritic steel using a contact transducer array. The highly heterogeneous structure of this material produces a strong scattering noise in ultrasound images. Furthermore, the surface waves guided along the array interfere with the bulk waves backscattered by defects. In order to overcome these problems, the DORT method is applied before calculating images with the STA algorithm. The method consists in analyzing in the frequency domain the singular values and singular vectors of the full array transfer matrix. This paper first presents an analysis of the singular values of different waves contained in the data acquisition, which facilitates the identification of the subspace associated with the surface guided waves for filtering operations. Then, a filtered matrix is defined where the contribution of structural noise and guided waves are reduced. Finally, in the time domain, the STA algorithm is applied to this matrix in order to calculate an image with reduced structural noise. Experiments demonstrate that this filtering improves the signal-to-noise ratio by more than 12 dB in comparison with the STA image before filtering.

Pseudoinverse Decoding Process in Delay-Encoded Synthetic Transmit Aperture Imaging.

Recently, we proposed a new method to improve the signal-to-noise ratio of the prebeamformed radio-frequency data in synthetic transmit aperture (STA) imaging: the delay-encoded STA (DE-STA) imaging. In the decoding process of DE-STA, the equivalent STA data were obtained by directly inverting the coding matrix. This is usually regarded as an ill-posed problem, especially under high noise levels. Pseudoinverse (PI) is usually used instead for seeking a more stable inversion process. In this paper, we apply singular value decomposition to the coding matrix to conduct the PI. Our numerical studies demonstrate that the singular values of the coding matrix have a special distribution, i.e., all the values are the same except for the first and last ones. We compare the PI in two cases: complete PI (CPI), where all the singular values are kept, and truncated PI (TPI), where the last and smallest singular value is ignored. The PI (both CPI and TPI) DE-STA processes are tested against noise with both numerical simulations and experiments. The CPI and TPI can restore the signals stably, and the noise mainly affects the prebeamformed signals corresponding to the first transmit channel. The difference in the overall enveloped beamformed image qualities between the CPI and TPI is negligible. Thus, it demonstrates that DE-STA is a relatively stable encoding and decoding technique. Also, according to the special distribution of the singular values of the coding matrix, we propose a new efficient decoding formula that is based on the conjugate transpose of the coding matrix. We also compare the computational complexity of the direct inverse and the new formula.

Axial motion estimation and compensation method for synthetic aperture sequential beamforming LaTeX submissions to Electronics Letters

Synthetic aperture sequential beamforming (SASB) is a two-stage delay-and-sum beamforming procedure, which can be applied to B-mode imaging with an implementation of low complexity compared to the traditional synthetic transmit aperture imaging. A new SASB imaging scheme in order to compensate the effects of axial motion is proposed. The velocity and direction of the motion can be evaluated by cross-correlation between specific beams according to adjacent focus of the SASB. The performance assessment, conducted by using simulated data, reveals that the proposed method can correct the positions of tissue motion without extra firings.

Delay-encoded transmission and image reconstruction method in synthetic transmit aperture imaging.

Synthetic transmit aperture (STA) imaging systems usually have a lower SNR compared with conventional Bmode ultrasound systems because only one or a small number of elements are selected for each transmission in STA. Here we propose delay-encoded synthetic transmit aperture (DE-STA) imaging to encode all the transmission elements to increase the SNR of the pre-beamformed RF signals. The encoding scheme is similar to the Hadamard encoding. However, in each transmission of DE-STA imaging, selected transmitting elements are delayed by a half period of the ultrasound wave relative to the rest transmitting elements, rather than using a pulse inversion as in the Hadamard encoding sequence. After all the transmission events, a decoding process in the temporal frequency domain is applied to the acquired RF signals to recover the equivalent traditional STA signals with a better SNR. The proposed protocol is tested with simulated data (using Field II) and experimental data acquired with a commercial linear array imaging system (Ultrasonix RP). The results from both the simulations and the experiments demonstrate increased SNR of pre-beamformed RF signals and improved image quality in terms of peak signal-to-noise ratio (PSNR), resolution and contrast-to-noise ratio compared with traditional STA. The lateral resolution (as assessed by a wire target) of DESTA imaging is improved by 28% and the PSNR of the wire is increased by 7 dB, respectively, compared with traditional STA imaging. The proposed image reconstruction framework can also be extended to other transmission protocols.