Delay Multiply And Sum Beamformer Research Articles

Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence.

For ultrasound multi-angle plane wave (PW) imaging, the coherent PW compounding (CPWC) method provides limited image quality because of its conventional delay-and-sum beamforming. The delay-multiply-and-sum (DMAS) method is a coherence-based algorithm that improves image quality by introducing signal coherence among either receiving channels or PW transmit angles into the image output. The degree of signal coherence in DMAS is conventionally a global value for the entire image and thus the image resolution and contrast in the target region improves at the cost of speckle quality in the background region. In this study, the adaptive DMAS (ADMAS) is proposed such that the degree of signal coherence relies on the local characteristics of the image region to maintain the background speckle quality and the corresponding contrast-to-noise ratio (CNR). Subsequently, the ADMAS algorithm is further combined with minimum variance (MV) beamforming to increase the image resolution. The optimal MV estimation is determined to be in the direction of the PW transmit angle (Tx) for multi-angle PW imaging. Our results show that, using the PICMUS dataset, TxMV-ADMAS beamforming significantly improves the image quality compared with CPWC. When the p value is globally fixed to 2 as in conventional DMAS, though the main-lobe width and the image contrast in the experiments improve from 0.57 mm and 27.0 dB in CPWC, respectively, to 0.24 mm and 38.0 dB, the corresponding CNR decreases from 12.8 to 11.3 due to the degraded speckle quality. With the proposed ADMAS algorithm, however, the adaptive p value in DMAS beamforming helps to restore the CNR value to the same level of CPWC while the improvement in image resolution and contrast remains evident.

Improved source localization in passive acoustic mapping using delay-multiply-and-sum beamforming with virtually augmented aperture

High-intensity focused ultrasound (HIFU) is a promising non-invasive treatment method whose applications include tissue ablation, hemostasis, thrombolysis and blood–brain barrier opening etc. Its therapeutic effects come from the thermal necrosis and the mechanical destruction associated with acoustic cavitation. Passive acoustic mapping (PAM) is capable of simultaneous monitoring of HIFU-induced cavitation events using only receive beamforming. Nonetheless, conventional time exposure acoustics (TEA) algorithm has poor spatial resolution and suffers from the X-shaped artifacts. These factors lead to difficulties in precise localization of cavitation source. In this study, we proposed a novel adaptive PAM method which combines Delay-Multiply-and-Sum (DMAS) beamforming with virtual augmented aperture (VA) to overcome the problem. In DMAS-VA beamforming, the magnitude of each channel waveform is scaled by p-th root while the phase is multiplied by L. The p and L correspond respectively to the degree of signal coherence in DMAS beamforming and the augmentation factor of aperture size. After channel sum, p-th power is applied to restore the dimensionality of source strength and then the PAM image is reconstructed by accumulating the signal power over the observation time. Based on simulation and experimental results, the proposed DMAS-VA has better image resolution and image contrast compared with the conventional TEA. Moreover, since the VA method may introduce grating lobes into PAM because of the virtually augmented pitch size, DMAS coherent factor (DCF) is further developed to alleviate these image artifacts. Results indicate that, with DCF weighting, the PAM image of DMAS-VA beamforming could be constructed without detectable image artifacts from grating lobes and false main lobes.

Location of Early Stage Tumor Detection using Microwave Imaging in the Breast Phantom.

Universally, the most predominant cause of female mortality is mainly due to breast cancer. Owing to numerous constraints in the existing imaging technique, researchers are trying out an alternative tool to detect the tumor before going to the miserable stage. This article presents a novel method to detect the mean value system for detecting the location of the tumor in different depths by shifting the antenna anywhere in the breast tissue. In addition, an algorithm to reconstruct the breast image, namely Delay-Multiply-and-Sum (DMAS) is followed to identify the tumor implanted in the breast tissue. The analysis shows that the maximum mean value occurs while the antenna moves very near to the tumor while the mean value reduces while the antenna shifts apart from the tumor location. The mean value in different locations is converted into a microwave image. The high intensity in the image exhibits the precise position of the tumor. This technique can identify the location of early-stage tumor of size 3mm. Multiple tumors of sizes 6mm and 7mm can identify at a depth of 12mm and 18mm in the homogeneous breast phantom. DMAS can provide better imaging results in the early stage tumor of size 3mm embedded in the breast phantom. Microwave imaging is an efficient technique to differentiate healthy and malignant tissue in the breast. Antenna plays a major role in identifying tumors in the breast in the early stage. Hence a high-performance Ultra Wideband Dielectric Resonator Antenna (DRA-UWB) is used to identify the tumor in the breast. An antenna is sketched in different locations of the breast phantom. On account of the hemispherical structure, the mean value of the reflected signal is high at the center than at the edge. Hence, the difference in mean value is calculated with and without breast phantom for identifying the tumor location. The overall efficiency of this technique can be improved by using a high-performance UWB antenna. The image of the breast is reformed by the DMAS beamforming algorithm.

Higher-order correlation based real-time beamforming in photoacoustic imaging.

Although a delay-and-sum (DAS) beamformer is best suited for real-time photoacoustic (PA) image formation, the reconstructed images are often afflicted by noises, sidelobes, and other intense artifacts due to inaccurate assumptions in PA signal correlation. The present work aims to develop a reconstruction method that reduces the occurrence of sidelobes and artifacts and thus improves the reconstructed image quality or imaging performance. This beamformer is fundamentally based on higher-order signal correlation wherein a higher number of delayed PA signals-compared to conventional delay-multiply-and-sum (DMAS)-are combined and summed up. The proposed technique provides significant improvements in resolution, contrast, and signal-to-noise ratio (SNR) compared to traditional beamformers. For real-time implementation, the proposed algorithms were simplified, and their computational complexities were shrunk to the order of DAS [O(N)]. A GPU based study was also performed to validate the real-time capability of the proposed beamformers. For validation studies, both numerical simulation and experiments were conducted. Quantitative evaluation studies involving SNR, contrast ratio, generalized contrast-to-noise ratio, and FWHM demonstrate that the proposed higher-order DMAS beamformer is superior in PA image reconstruction. Conclusively, the proposed beamformer uniquely facilitates real-time PA image reconstruction with an achievable frame rate close to DAS and DMAS but with better imaging performance, which holds promise for real-time PA imaging and its clinical applications.

Sign coherence factor‐based double‐stage delay multiply and sum beamforming algorithm for breast cancer detection

AbstractThe delay‐multiply‐and‐sum (DMAS) beamforming algorithm has been extensively used in medical imaging. In this study, we proposed a fast double‐stage DMAS beamformer for breast cancer detection, combined with the sign coherence factor (SCF), namely SCF‐DMAS. The performance of this method was evaluated on a three‐dimensional‐printed breast phantom surrounded by evenly spaced circular array antennas. The results show that the proposed algorithm outperforms the other beamformers involved with respect to the signal‐to‐clutter Ratio, signal‐to‐mean ratio, and localization error. To summarize, the SCF‐DMAS improves the resolution and sidelobe suppression without significantly increasing the computational complexity.

A novel sophisticated form of DMAS beamformer: Application to breast cancer detection

Confocal microwave imaging (CMI) has the potential to be an alternative or complementary method for mammography in breast cancer screening. Data acquisition in CMI is very fast, safe, and comfortable for patients, but the reconstructed images are not always of high quality. High level of artifacts and poor resolution cause impaired quality. In this work, a novel, fast and robust beamformer, DMAS-D4 is presented. Delay-multiply-and-sum-degree-4 (DMAS-D4) is a next generation beamformer that expands the two-dimensional summations in delay-multiply-and-sum (DMAS) to four-dimensional summations in which all possible fourth degree terms are summed to increase robustness and resolution. A computationally-efficient implementation is presented which mitigates the additional computation required by DMAS. Furthermore, the proposed method can run iteratively which makes the ability to update the result using new observations. An idealized simulation compares basic performance of the proposed method with two other beamformers: (1) DAS, which is the gold standard, and (2) DMAS, which has been reported as the best beamformer so far. The results demonstrate that the DMAS-D4 achieves higher contrast and finer resolution. The proposed method increased the signal-to-max-ratio (SMXR) from 3.1 dB using DMAS to 5.7 dB in the heterogeneous breast mimicking phantom which illustrates the higher tumor detectability using the proposed method. Similarly, the Signal-to-Clutter Ratio (SCR) is 23.9 dB higher using the proposed method. By exploiting DMAS-D4 these benefits and potentially enhancing clinical decisions are attainable by the same computational load order as DAS. These results may be useful to inform future microwave breast imaging beamformer design.

DMAS Beamforming with Complementary Subset Transmit for Ultrasound Coherence-Based Power Doppler Detection in Multi-Angle Plane-Wave Imaging.

Conventional ultrasonic coherent plane-wave (PW) compounding corresponds to Delay-and-Sum (DAS) beamforming of low-resolution images from distinct PW transmit angles. Nonetheless, the trade-off between the level of clutter artifacts and the number of PW transmit angle may compromise the image quality in ultrafast acquisition. Delay-Multiply-and-Sum (DMAS) beamforming in the dimension of PW transmit angle is capable of suppressing clutter interference and is readily compatible with the conventional method. In DMAS, a tunable p value is used to modulate the signal coherence estimated from the low-resolution images to produce the final high-resolution output and does not require huge memory allocation to record all the received channel data in multi-angle PW imaging. In this study, DMAS beamforming is used to construct a novel coherence-based power Doppler detection together with the complementary subset transmit (CST) technique to further reduce the noise level. For p = 2.0 as an example, simulation results indicate that the DMAS beamforming alone can improve the Doppler SNR by 8.2 dB compared to DAS counterpart. Another 6-dB increase in Doppler SNR can be further obtained when the CST technique is combined with DMAS beamforming with sufficient ensemble averaging. The CST technique can also be performed with DAS beamforming, though the improvement in Doppler SNR and CNR is relatively minor. Experimental results also agree with the simulations. Nonetheless, since the DMAS beamforming involves multiplicative operation, clutter filtering in the ensemble direction has to be performed on the low-resolution images before DMAS to remove the stationary tissue without coupling from the flow signal.

Ultrasound DMAS Beamforming for Estimation of Tissue Speed of Sound in Multi-Angle Plane-Wave Imaging

Various methods have been proposed to estimate the tissue speed of sound (SOS) of propagating medium using the curvature of received channel waveform or the analysis of resultant image quality. In our previous study, baseband delay-multiply-and-sum (DMAS) beamforming methods have been developed for multi-angle plane-wave (PW) imaging which relies on signal coherence among transmit events (Tx-DMAS) or receive channel (Rx-DMAS) or both (2D-DMAS) to suppress low-coherence clutters. In this study, we further extend our DMAS beamforming to quantify the level of signal coherence for determining the average SOS in multi-angle PW imaging. The signal coherence in multi-angle PW imaging is represented as the DMAS coherence factor (DCF) which can be easily estimated from the magnitude ratio of the pixel value of DMAS image to that of DAS image. By searching the beamforming velocity that provides the highest signal coherence of echo matrix, the average tissue SOS of the imaged object can be determined. For the PICMUS experimental dataset, the optimal beamforming velocity (Copt) estimated by the proposed DCF method does provide the best image quality. For the Prodigy dataset, the estimated tissue SOS is 1426 ± 6 m/s which is very close to the actual tissue SOS of 1427 m/s and the estimated SOS also corresponds to the Copt with the minimal −6-dB lateral width and the maximal contrast within an error of 10 m/s. Estimation of tissue SOS in the proposed DCF method is also robust even in the presence of transmit delay error due to deviation of SOS.

A Study of Double-Stage DMAS and p-DMAS for Their Relation in Baseband Ultrasound Beamforming

Delay-multiply-and-sum (DMAS) imaging is capable of suppressing clutter interference by introducing spatial coherence of received channel data into the beamforming process. Recently, double-stage DMAS beamforming (DS-DMAS) has been proposed by firstly calculating the column sum of auto-covariance matrix and then applying DMAS in the second stage to further highlight the channel coherence. In contrast, p-DMAS beamforming emphasizes the spatial coherence by adopting a single-stage p-th-root magnitude scaling of the channel signal and p-th-power restoration after channel sum. Though their implementation differs, DS-DMAS and p-DMAS produce visually similar image quality. In this study, the relation between DS-DMAS and p-DMAS is analytically demonstrated and verified using simulations and experiments. Results indicate that DS-DMAS beamforming is virtually equivalent to p-DMAS with p = 3 particularly when high coherent target such as wire reflectors are being imaged. Reconstructed B-mode image and corresponding quantitative metrics also suggest high similarity between DS-DMAS and p-DMAS for speckle-generating object. For numerical B-mode image, their absolute difference is below −43.5 dB for wire reflectors and −42.6 dB for pure speckle phantom. Due to their virtually equivalent performance, p-DMAS beamforming is a better alternative than DS-DMAS in terms of computational complexity.

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.

Two-Dimensional Spatial Coherence for Ultrasonic DMAS Beamforming in Multi-Angle Plane-Wave Imaging

Ultrasonic multi-angle plane-wave (PW) coherent compounding relies on delay-and-sum (DAS) beamforming of two-dimensional (2D) echo matrix in both the dimensions PW transmit angle and receiving channel to construct each image pixel. Due to the characteristics of DAS beamforming, PW coherent compounding may suffer from high image clutter when the number of transmit angles is kept low for ultrafast image acquisition. Delay-multiply-and-sum (DMAS) beamforming exploits the spatial coherence of the receiving aperture to suppress clutter interference. Previous attempts to introduce DMAS beamforming into multi-angle PW imaging has been reported but only in either dimension of the 2D echo matrix. In this study, a novel DMAS operation is proposed to extract the 2D spatial coherence of echo matrix for further improvement of image quality. The proposed 2D-DMAS method relies on a flexibly tunable p value to manipulate the signal coherence in the beamforming output. For p = 2.0 as an example, simulation results indicate that 2D-DMAS outperforms other one-dimensional DMAS methods by at least 9.3 dB in terms of ghost-artifact suppression. Experimental results also show that 2D-DMAS provides the highest improvement in lateral resolution by 32% and in image contrast by 15.6 dB relative to conventional 2D-DAS beamforming. Nonetheless, since 2D-DMAS emphasizes signal coherence more than its one-dimensional DMAS counterparts, it suffers from the most elevated speckle variation and the granular pattern in the tissue background.

Real-time delay-multiply-and-sum beamforming with coherence factor for in vivo clinical photoacoustic imaging of humans

In the clinical photoacoustic (PA) imaging, ultrasound (US) array transducers are typically used to provide B-mode images in real-time. To form a B-mode image, delay-and-sum (DAS) beamforming algorithm is the most commonly used algorithm because of its ease of implementation. However, this algorithm suffers from low image resolution and low contrast drawbacks. To address this issue, delay-multiply-and-sum (DMAS) beamforming algorithm has been developed to provide enhanced image quality with higher contrast, and narrower main lobe compared but has limitations on the imaging speed for clinical applications. In this paper, we present an enhanced real-time DMAS algorithm with modified coherence factor (CF) for clinical PA imaging of humans in vivo. Our algorithm improves the lateral resolution and signal-to-noise ratio (SNR) of original DMAS beamformer by suppressing the background noise and side lobes using the coherence of received signals. We optimized the computations of the proposed DMAS with CF (DMAS-CF) to achieve real-time frame rate imaging on a graphics processing unit (GPU). To evaluate the proposed algorithm, we implemented DAS and DMAS with/without CF on a clinical US/PA imaging system and quantitatively assessed their processing speed and image quality. The processing time to reconstruct one B-mode image using DAS, DAS with CF (DAS-CF), DMAS, and DMAS-CF algorithms was 7.5, 7.6, 11.1, and 11.3 ms, respectively, all achieving the real-time imaging frame rate. In terms of the image quality, the proposed DMAS-CF algorithm improved the lateral resolution and SNR by 55.4% and 93.6 dB, respectively, compared to the DAS algorithm in the phantom imaging experiments. We believe the proposed DMAS-CF algorithm and its real-time implementation contributes significantly to the improvement of imaging quality of clinical US/PA imaging system.

Ultrasound Baseband Delay-Multiply-and-Sum (BB-DMAS) nonlinear beamforming

Compared to conventional Delay-and-Sum (DAS) beamforming, Delay-Multiply-and-Sum (DMAS) imaging uses multiplicative coupling of channel pairs for spatial coherence of receiving aperture to improve image resolution and contrast. However, present DMAS imaging is based on the radio-frequency (RF) channel signals (RF-DMAS) and thus requires large oversampling to avoid aliasing and switching of band-pass filtering to isolate the corresponding spectral components for imaging. Baseband DMAS (BB-DMAS) beamforming in this study is based on the demodulated channel signals to provide similar results but with simplified signal processing. The BB-DMAS beamforming scales the magnitude of time-delayed channel signal by p-th root while maintaining the phase. After channel sum, the output dimensionality is restored by p-th power. The multiplicative coupling in BB-DMAS always renders baseband signal and thus the need for oversampling is eliminated. Besides, the BB-DMAS can use any rational p values to provide flexible image quality and an explicit relation between BB-DMAS beamforming and channel-domain phase coherence exists. Our results show that the image characteristics between BB-DMAS and RF-DMAS are similar. The suppression of lateral side lobe level, grating lobe level and uncorrelated random noises gradually increases with the rational p value in BB-DMAS beamforming. The image contrast improves from −24.8 dB in DAS to −34.3 dB, −43.0 dB and −51.4 dB in BB-DMAS, respectively with p value of 1.5, 2.0 and 2.5. In conclusion, BB-DMAS beamforming provides flexible manipulation of image quality by introducing baseband spatial coherence in the ultrasonic imaging.

Double-Stage Delay Multiply and Sum Beamforming Algorithm Applied to Ultrasound Medical Imaging

In ultrasound (US) imaging, delay and sum (DAS) is the most common beamformer, but it leads to low-quality images. Delay multiply and sum (DMAS) was introduced to address this problem. However, the reconstructed images using DMAS still suffer from the level of side lobes and low noise suppression. Here, a novel beamforming algorithm is introduced based on expansion of the DMAS formula. We found that there is a DAS algebra inside the expansion, and we proposed use of the DMAS instead of the DAS algebra. The introduced method, namely double-stage DMAS (DS-DMAS), is evaluated numerically and experimentally. The quantitative results indicate that DS-DMAS results in an approximately 25% lower level of side lobes compared with DMAS. Moreover, the introduced method leads to 23%, 22% and 43% improvement in signal-to-noise ratio, full width at half-maximum and contrast ratio, respectively, compared with the DMAS beamformer.

An efficient subarray average delay multiply and sum beamformer algorithm in ultrasound imaging

Beamformer plays an important role in medical ultrasound imaging systems. The delay multiply and sum (DMAS) beamformer achieves better performance in contrast and resolution compared with the delay and sum (DAS) beamformer, but suffers from higher computational complexity and partial energy loss. The higher computational complexity mainly arises from the multiply and geometric average operation, which needs (N2-N)/2 computations at every point, where N denotes the number of array elements. The partial energy loss, mainly due to the autocorrelation component of the echo signals, has been neglected in the DMAS beamformer. In this paper, we propose a subarray average delay multiply and sum (SA-DMAS) beamformer which is combined with subarray average technique of covariance matrix and DMAS beamformer. This will lower the computational complexity, while keeping the side lobe suppressing property of DMAS. The main idea of the proposed method is adding autocorrelation component of the echo signals to DMAS, and converting the expression in covariance matrix form. The subarray average technique is used to estimate the covariance matrix of the echo signals. The field II simulation of point targets and cyst phantoms was used to prove the performance of the proposed method. An RF data experiment was applied to support the feasibility and validity of our method. The simulation and experimental results show that our method has a lower computational complexity as O(9/2L2) , where L denotes the sub-array size, and has equivalent performance like the MV and DMAS beamformer.

Ultrasound plane-wave imaging with delay multiply and sum beamforming and coherent compounding.

Improving the frame rate is an important aspect in medical ultrasound imaging, particularly in 3D/4D cardiac applications. However, an accurate trade-off between the higher frame rate and image contrast and resolution should be performed. Plane-Wave Imaging (PWI) can potentially achieve frame rates in the order of 10 kHz, as it uses a single unfocused plane wave (and thus a single transmit event) to acquire the image of the entire region of interest. The lack of transmit focusing however causes a significant drop of image quality, which can be restored by coherently compounding several tilted plane-wave frames, at the expense of the frame rate. PWI together with the use of a beamforming algorithm able to achieve a higher image contrast resolution, such as the Delay Multiply And Sum (DMAS), could thus allow to improve image quality achieving a high frame rate at the same time. This paper presents the first simulation results obtained by employing DMAS beamforming and PWI with different transmission angles and coherent compounding. The simulated Point Spread Function (PSF) and cyst-phantom images show that DMAS makes it possible to achieve a high image quality with a reduced number of compounded frames compared to standard Delay And Sum (DAS), and hence it can be used to improve the contrast and resolution of plane-wave images still achieving a very high frame rate.

Ultrasound Synthetic Aperture Focusing with the Delay Multiply and sum beamforming algorithm.

The Delay Multiply and Sum (DMAS) beamforming algorithm was originally conceived for microwave imaging of breast cancer. In a previous work, we demonstrated that, by properly modifying and improving the algorithm processing steps, DMAS can be successfully applied to ultrasound signals for B-mode image formation and that it outperforms standard Delay and Sum (DAS) beamforming in terms of contrast resolution. As previously pointed out, however, DMAS-beamformed B-mode images, in which fixed and dynamic focusing are applied respectively during transmit and receive operations, show an intensity drop away from the transmit focal depth compared to DAS images. This could be due to the fact that DMAS beamforming is based on a measure of backscattered signal coherence, which reaches its maximum only at the transmit focus, where signals are perfectly realigned. The preliminary results presented in this work show that, by employing Synthetic Aperture Focusing (SAF), which allows to achieve dynamic focusing both on transmission and reception, this intensity loss is compensated, as DAS and DMAS images have almost the same maximum amplitude level at all depths.

The delay multiply and sum beamforming algorithm in ultrasound B-mode medical imaging.

Most of ultrasound medical imaging systems currently on the market implement standard Delay and Sum (DAS) beamforming to form B-mode images. However, image resolution and contrast achievable with DAS are limited by the aperture size and by the operating frequency. For this reason, different beamformers have been presented in the literature that are mainly based on adaptive algorithms, which allow achieving higher performance at the cost of an increased computational complexity. In this paper, we propose the use of an alternative nonlinear beamforming algorithm for medical ultrasound imaging, which is called Delay Multiply and Sum (DMAS) and that was originally conceived for a RADAR microwave system for breast cancer detection. We modify the DMAS beamformer and test its performance on both simulated and experimentally collected linear-scan data, by comparing the Point Spread Functions, beampatterns, synthetic phantom and in vivo carotid artery images obtained with standard DAS and with the proposed algorithm. Results show that the DMAS beamformer outperforms DAS in both simulated and experimental trials and that the main improvement brought about by this new method is a significantly higher contrast resolution (i.e., narrower main lobe and lower side lobes), which turns out into an increased dynamic range and better quality of B-mode images.