Filtered-Delay Multiply And Sum Research Articles

Beam multiply and sum: A tradeoff between delay and sum and filtered delay multiply and sum beamforming for ultrafast ultrasound imaging

The delay and sum (DAS) has been the popular beamforming algorithm for image reconstruction in ultrafast ultrasound imaging systems due to its low complexity implementation. However, to improve the lower contrast and resolution in images reconstructed using DAS, there have been many adaptive and non-linear beamforming algorithms developed in the recent past. One of the popular non-linear algorithms proposed in the literature, filtered delay multiply and sum (F-DMAS) is sensitive to off-axis clutters and produces artifacts that result in the degradation of the overall image quality along with a possible dynamic range alteration. In this work, a novel approach to combining the strengths of DAS and F-DMAS algorithms is proposed. The proposed approach referred to as beam multiply and sum (BMAS), employs a DAS beamformer in multiple sub-apertures at receive to form the sub-aperture beams and cross multiplies them using a multiply and sum architecture to enhance the spatial coherence and suppress the clutter artifacts. An exhaustive performance comparison in terms of dynamic range alteration, resolution, and contrast of the BMAS is performed with standard in-silico and in-vitro datasets. The results suggest that the proposed approach outperforms the DAS and F-DMAS beamformers in most cases. More than the proposal of a novel beamforming algorithm, to the best of our knowledge, the approach is the first attempt of its kind towards the possibility of the co-existence of two or more beamformers in an ultrasound imaging system. With optimal tuning, it could provide a good trade-off between the effects of improved resolution and improved contrast while keeping the dynamic range linearity unaltered.

Enhancement of Ultrasound B-Mode Image Quality Using Nonlinear Filtered-Multiply-and-Sum Compounding for Improved Carotid Artery Segmentation.

In ultrasound B-mode imaging, the axial resolution (AR) is commonly determined by the duration or bandwidth of an excitation signal. A shorter-duration pulse will produce better resolution compared to a longer one but with compromised penetration depth. Instead of relying on the pulse duration or bandwidth to improve the AR, an alternative method termed filtered multiply and sum (FMAS) has been introduced in our previous work. For spatial-compounding, FMAS uses the autocorrelation technique as used in filtered-delay multiply and sum (FDMAS), instead of conventional averaging. FMAS enables a higher frame rate and less computational complexity than conventional plane-wave compound imaging beamformed with delay and sum (DAS) and FDMAS. Moreover, it can provide an improved contrast ratio and AR. In previous work, no explanation was given on how FMAS was able to improve the AR. Thus, in this work, we discuss in detail the theory behind the proposed FMAS algorithm and how it is able to improve the spatial resolution mainly in the axial direction. Simulations, experimental phantom measurements and in vivo studies were conducted to benchmark the performance of the proposed method. We also demonstrate how the suggested new algorithm may be used in a practical biomedical imaging application. The balloon snake active contour segmentation technique was applied to the ultrasound B-mode image of a common carotid artery produced with FMAS. The suggested method is capable of reducing the number of iterations for the snake to settle on the region-of-interest contour, accelerating the segmentation process.

Pixel-based approach to delay multiply and sum beamforming in combination with Wiener filter for improving ultrasound image quality

Unified pixel-based (PB) beamforming has been implemented for ultrasound imaging, offering significant enhancements in lateral resolution compared to the conventional dynamic focusing. However, it still suffers from clutter and off-axis artifacts, limiting the contrast resolution. This paper proposes an efficient method to improve image quality by integrating filtered delay multiply and sum (F-DMAS) into the framework. This hybrid strategy incorporates the spatial coherence of the received data into the beamforming process to improve contrast resolution and clutter rejection in the generated image. We also integrate a Wiener filter to suppress the spatiotemporal spreading using signals echoed from a single scatterer at the transmit focus as a kernel for the deconvolution. The Wiener filter is applied to the received waveforms before performing the hybrid strategy. The Wiener filter is shown to reduce interference due to the interaction between the excitation pulse and the transfer functions of the transducer elements, thus benefiting the axial resolution of the generated images. We validate the proposed method and compare it with other beamforming strategies through a series of experiments, including simulation, phantom, and in vivo studies. The results show that our approach can substantially improve both spatial resolution and contrast over the unified PB algorithm, while still maintaining the good features of this beamformer. The simplicity and good performance of our method show its potential for use in clinical applications.

Correlation-based modified delay-multiply-and-sum beamforming applied to medical ultrasound imaging

Background and objective: Recently, the Filtered Delay-Multiply-and-Sum (F-DMAS) beamformer was successfully applied to Ultrasound Imaging (UI), improving the image quality compared to the conventional data-independent Delay-and-Sum (DAS) beamformer. However, its reconstructed images lead to restricted resolution, contrast, and dark regions in the speckle. Various beamformers based on F-DMAS were proposed to mitigate these issues; some improved resolution and contrast at the expense of more dark regions; others reduced the dark points with lower contrast than the F-DMAS beamformer. This study aims to propose a novel beamformer, improving resolution and contrast while reducing dark points in the speckle.Methods: This study proposes a modified version of the F-DMAS beamformer, using two modifications to compensate for the aforesaid trade-off. Firstly, coupled signals’ Correlation Coefficient (CC) was calculated and compared to a threshold value. The multiplications were applied only to the high-correlated (those whose CC is higher than the threshold value) signals. Secondly, a new Modified Coherence Factor (MCF) was applied to the high-correlated signals. Then, these two new beamformers were combined to reach a novel beamformer entitled “Modified DMAS (MDMAS).”Results: The performance of MDMAS was evaluated using simulating Point-Spread-Function, Cyst phantom, the experimental geabr dataset, and an in vivo dataset. Moreover, we evaluated the performance of the MDMAS beamformer quantitatively. Full-width-half-maximum (FWHM), contrast-ratio (CR), contrast-to-noise-ratio (CNR), speckle signal-to-noise-ratio (sSNR), and generalized-CNR (gCNR) were assessed.Conclusions: This paper modified the conventional F-DMAS beamformer by adaptively multiplying signals. Then, CF was implemented on high correlated signals (MCF) and combined with the adaptive beamformer to compensate for the poor contrast. Results highlight that the MDMAS beamformer outperforms F-DMAS in terms of resolution and contrast without compromising the speckle from the dark region artifact.

Novel spatio-temporal non-linear beamformers for sparse synthetic aperture ultrasound imaging

The development of two modified non-linear beamformers, Spatio-Temporal Delay Multiply and Sum (ST-DMAS) and Spatio-Temporal Delay Euclidian-Weighted Multiply and Sum (ST-DewMAS) is reported in this paper. A sparse-transmit scheme (with only 8 transmits) on Synthetic Transmit Aperture technique (sparse STA) was chosen to evaluate the beamformers ability to generate the high-resolution Ultrasound image. These methods allow for obtaining superior-quality imaging at enhanced frame rates. The different beamformers of ST-DewMAS, ST-DMAS, Filtered Delay Multiply and Sum (F-DMAS), and Delay and Sum (DAS), were compared in terms of the Axial and Lateral Resolutions, AR and LR, respectively, Contrast-to-Noise Ratio (CNR), Contrast Ratio (CR), and Generalized CNR (GCNR). Experimental results demonstrate that the developed ST-DMAS and ST-DewMAS reconstruction on sparse STA technique resulted in better quality images compared to those obtained using DAS and F-DMAS. Specifically, the metrics of AR, LR CR, CNR, and GCNR showed improvements of more than 25% (for ST-DMAS) and 40 % (for ST-DewMAS) over those from DAS and F-DMAS beamformed images, respectively. Thus, the results demonstrate that the frame rate and image quality of an US system can both be enhanced by ST-DewMAS compared to the beamformers of F-DMAS and DAS.

A Low-Complexity and High-Resolution Beamformer for Portable Medical Ultrasound Imaging.

So far, researchers have proposed various methods to improve the quality of medical ultrasound imaging. However, in portable medical ultrasound imaging systems, features, such as low cost and low power consumption for battery longevity, are very important. Hence, most of the proposed algorithms have not been proper substitutes for the delay and sum (DAS) algorithm in portable clinical applications due to their high computational complexity and cost. In this article, a new algorithm is presented concentrating on reducing the computational complexity based on a technique that separates the signal from the correlated interferences to overcome the negative characteristics, particularly for portable applications such as high price, high power consumption, and off-axis clutters in the azimuth direction. Also, the proposed algorithm yields a higher contrast compared to that of the DAS algorithm while achieving a similar computation complexity order of O ( n ) similar to the DAS algorithm. Furthermore, the performed simulations confirm that the proposed method is able to achieve a better resolution almost twice as that of the filtered delay multiply and sum (F-DMAS) algorithm with the same sidelobe level.

Ultrasonic pseudo-color imaging in strongly attenuating materials with Filtered-Delay Multiply And Sum nonlinear beamforming

To detect flaws in strongly attenuating materials, we propose an ultrasonic phased array imaging method that combines Filtered-Delay Multiply And Sum (F-DMAS) nonlinear beamforming algorithm with pseudo-color technique. Based on the spatial coherence of signals, three filters with different frequency ranges are selected to reconstruct F-DMAS images from the full matrix capture (FMC) data. Then, three channels of F-DMAS images are combined with the RGB color model to obtain the pseudo-color image. Finally, an automatic flaw extraction algorithm is developed using the techniques of color image segmentation, data fusion, and edge detection. Experiments are performed on samples of polymer bonded explosives with side drilled holes. The results show that the proposed method has significant advantages over the linear beamformed Total Focusing Method (TFM) in terms of signal-to-noise ratio, detection ability, and visual presentation of flaws.

Optimally-weighted non-linear beamformer for conventional focused beam ultrasound imaging systems

A novel non-linear beamforming method, namely, filtered delay optimally-weighted multiply and sum (F-DowMAS) beamforming is reported for conventional focused beamforming (CFB) technique. The performance of F-DowMAS was compared against delay and sum (DAS), filtered delay multiply and sum (F-DMAS), filtered delay weight multiply and sum (F-DwMAS) and filter delay Euclidian weighted multiply and sum (F-DewMAS) methods. Notably, in the proposed method the optimal adaptive weights are computed for each imaging point to compensate for the effects due to spatial variations in beam pattern in CFB technique. F-DowMAS, F-DMAS, and DAS were compared in terms of the resulting image quality metrics, Lateral resolution (LR), axial resolution (AR), contrast ratio (CR) and contrast-to-noise ratio (CNR), estimated from experiments on a commercially available tissue-mimicking phantom. The results demonstrate that F-DowMAS improved the AR by 57.04% and 46.95%, LR by 58.21% and 53.40%, CR by 67.35% and 39.25%, and CNR by 44.04% and 30.57% compared to those obtained using DAS and F-DMAS, respectively. Thus, it can be concluded that the newly proposed F-DowMAS outperforms DAS and F-DMAS. As an aside, we also show that the optimal weighting strategy can be extended to benefit DAS.

Optimizing the lateral beamforming step for filtered-delay multiply and sum beamforming to improve active contour segmentation using ultrafast ultrasound imaging

As an alternative to delay-and-sum beamforming, a novel beamforming technique called filtered-delay multiply and sum (FDMAS) was introduced recently to improve ultrasound B-mode image quality. Although a considerable amount of work has been performed to evaluate FDMAS performance, no study has yet focused on the beamforming step size, Δx, in the lateral direction. Accordingly, the performance of FDMAS was evaluated in this study by fine-tuning Δx to find its optimal value and improve boundary definition when balloon snake active contour (BSAC) segmentation was applied to a B-mode image in ultrafast imaging. To demonstrate the effect of altering Δx in the lateral direction on FDMAS, measurements were performed on point targets, a tissue-mimicking phantom and in vivo carotid artery, by using the ultrasound array research platform II equipped with one 128-element linear array transducer, which was excited by 2-cycle sinusoidal signals. With 9-angle compounding, results showed that the lateral resolution (LR) of the point target was improved by 67.9% and 81.2%, when measured at −6 dB and −20 dB respectively, when Δx was reduced from λ to λ/5. Meanwhile the image contrast ratio (CR) measured on the CIRS phantom was improved by 10.38 dB at the same Δx reduction and the same number of compounding angles. The enhanced FDMAS results with lower side lobes and less clutter noise in the anechoic regions provides a means to improve boundary definition on a B-mode image when BSAC segmentation is applied.

Applying Coherence Factor to Double-Stage Delay Multiply and Sum Beamforming in Medical Ultrasound Imaging

The Filtered Delay Multiply and Sum (F-DMAS) beamforming algorithm has recently been proposed to improve the resolution and contrast in ultrasound imaging. Based on F-DMAS, some researchers have introduced an alternative named Double-Stage Delay Multiply and Sum (DS-DMAS), which can be considered as an enhanced version of F-DMAS. The DS-DMAS expands the DMAS algorithm to synthesize some new signals, which are then beamformed using a DMAS beamformer. However, the way to generate new signals in DS-DMAS can be thought of as a Delay and Sum (DAS) operation. There are some shortages in the DAS algorithm, so we proposed a new approach named Coherence Factor based Double-Stage Delay Multiply and Sum (DSDMAS-CF) to address these issues. The key idea of our method is to optimize the DAS operation in DSDMAS. Therefore, a modified coherence factor (CF) is applied to weight each item in DS-DMAS. The simulation, experimental and in vivo data are used to compare the performance between DAS, F-DMAS, DS-DMAS and DS-DMAS-CF. The results show that the DS-DMAS-CF gets better resolution and contrast in comparison with the other three algorithms.

Generalized spatial coherence reconstruction for photoacoustic computed tomography.

.Significance: Coherence, a fundamental property of waves and fields, plays a key role in photoacoustic image reconstruction. Previously, techniques such as short-lag spatial coherence (SLSC) and filtered delay, multiply, and sum (FDMAS) have utilized spatial coherence to improve the reconstructed resolution and contrast with respect to delay-and-sum (DAS). While SLSC uses spatial coherence directly as the imaging contrast, FDMAS employs spatial coherence implicitly. Despite being more robust against noise, both techniques have their own drawbacks: SLSC does not preserve a relative signal magnitude, and FDMAS shows a reduced contrast-to-noise ratio.Aim: To overcome these limitations, our aim is to develop a beamforming algorithm—generalized spatial coherence (GSC)—that unifies SLSC and FDMAS into a single equation and outperforms both beamformers.Approach: We demonstrated the application of GSC in photoacoustic computed tomography (PACT) through simulation and experiments and compared it to previous beamformers: DAS, FDMAS, and SLSC.Results: GSC outperforms the imaging metrics of previous state-of-the-art coherence-based beamformers in both simulation and experiments.Conclusions: GSC is an innovative reconstruction algorithm for PACT, which combines the strengths of FDMAS and SLSC expanding PACT’s applications.

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

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

Image enhancement of photoacoustic imaging for early endometrial cancer detection by employing a filtered delay multiply and sum beamforming algorithm

In endometrial cancer, patients in early stages have a 91% 5-year survival chance. By contrast, patients in advanced stages have only 20% survival chance. Therefore, early diagnosis of endometrial cancer is very important. Photoacoustic imaging is able to distinguish benign from malignant tumors. However, the images acquired through photoacoustic imaging contain inherent artifacts, caused by imperfect reconstruction algorithms. In this paper, to improve the said images, a filtered delay-multiply-and-sum (F-DMAS) algorithm, which was proven to have an increased dynamic range and better quality of B-mode images was employed in the reconstruction process. First, the images of two blood vessel phantom experiments, acquired through photoacoustic imaging, were reconstructed by employing the F-DMAS algorithm. The results show the lateral resolutions of the system improving from 2.22 mm (with traditional photoacoustic imaging reconstruction algorithms) to 1.47 mm. Next, images of a pig uterus, filled with intralipid-20% emulsion, were also reconstructed by employing the F-DMAS algorithm. The average signal-to-noise ratio increased from 11.14 dB (with traditional photoacoustic imaging reconstruction algorithms) to 64.90 dB. In order to improve the continuity of the 3D PA image, F-DMAS with an adaptive coefficient was discussed to find the best balance between the signal-to-noise ratio and continuity. In conclusion, this paper demonstrates that the use of F-DMAS algorithms in the reconstruction of the images acquired through photoacoustic imaging in clinical investigations would improve the detection rate of early endometrial cancer.

Combining autocorrelation signals with delay multiply and sum beamforming algorithm for ultrasound imaging.

Beamformer is one of the most important components in ultrasound imaging system. The delay and sum (DAS) beamforming algorithm has been widely used in recent decades due to its simplicity and robustness. However, it has poor impact on resolution and contrast. A new beamformer named filtered delay multiply and sum (F-DMAS) which was an alternative of delay multiply and sum (DMAS) was proposed to overcome these shortcomings of DAS. Although F-DMAS partially enhances the image quality, its performance still has room for improvement. Therefore, a novel beamformer named lag-based delay multiply and sum (L-DMAS) which combines autocorrelation signals with DMAS algorithm is proposed by us to improve its efficiency. Field II was employed to synthesize a point target phantom and a cyst phantom to compare the performance between DAS, F-DMAS, double stage delay multiply and sum (DS-DMAS), and L-DMAS. We also estimate the performance of four algorithms on experimental data and in vivo data. These results show that both DS-DMAS and L-DMAS are better than DAS and F-DMAS in each case. In some cases, DS-DMAS and L-DMAS have little difference in performance, but in other cases, L-DMAS outperforms DS-DMAS. Graphical Abstract.

Filtered delay multiply and sum beamforming in high frame-rate ultrasound imaging

Filtered Delay Multiply and Sum (F-DMAS) is an ultrasound beamforming technique derived from microwave imaging, which exploits the spatial autocorrelation of the receive aperture to improve the quality of images. Being based on the spatial coherence of backscattered echoes, it reconstructs a pulse-echo beam with lower sidelobes and a narrower main lobe as compared to standard Delay and Sum (DAS). Thanks to this, F-DMAS can be effectively employed in high frame-rate (HFR) ultrasound imaging, where higher acquisition rates come together with more artifacts, lower contrast and worse spatial resolution. This presentation will provide an overview of the most recent applications of F-DMAS in HFR imaging, e.g., with multi-line transmission and plane-wave techniques. Results of simulations, phantom experiments and in vivo scans, particularly of cardiac imaging, show that F-DMAS represents an effective solution to improve image quality, suppress artifacts and increase the frame-rate at the same time. Moreover, two alternative methods, developed starting from the F-DMAS formulation, will be shown as they further enhance the image quality in HFR imaging.

Multi-line acquisition with delay multiply and sum beamforming in phased array ultrasound imaging, validation of simulation and in vitro

Increasing the frame rate of medical ultrasound imaging is very important, especially in applications such as cardiac diagnostic imaging, where such an imaging should be able to facilitate the examination of the temporal behaviour of the short cardiac cycle. Frame rate can be increased by the multi-line acquisition (MLA) method, also called parallel receive beamforming (PRB), where several beams are received from a single transmit (Tx) beam. The shortage is that imaging performance would be sacrificed. Filtered-delay multiply and sum (F-DMAS) is a non-linear beamforming technique proven to be able to improve the contrast and resolution of the image compared to traditional delay and sum (DAS) beamforming. In this paper, we proposed to combine MLA and the lower complexity F-DMAS algorithm, and use synthetic transmit beams (STB) to reduce the artifacts of MLA. The simulations of point targets and cyst phantoms were all carried out in Matlab using Field II. The results show that 2 line acquisition with delay multiply and sum (DMAS 2MLA) beamforming presents an equivalent imaging performance to that of traditional DMAS beamforming, and obtains a 7.69% higher resolution and 2 times higher contrast ratio in comparison to DAS beamforming. A real RF data experiment was applied to support the feasibility and validity of our method. The low complexity of F-DMAS (O(N)) would make it easy to implement 2 parallel beamformers. Thus, by combining 2MLA and F-DMAS, the frame rate can be improved to 2-fold higher with a better image quality compared to that of DAS beamforming.

High-Resolution Fast Ultrasound Imaging With Adaptive-Lag Filtered Delay-Multiply-and-Sum Beamforming and Multiline Acquisition.

Multiline acquisition (MLA) is a well-established method for a high-frame-rate cardiac ultrasound imaging, which is commonly used in conjunction with delay-and-sum (DAS) beamforming. The block-like artifacts that occur secondary to the use of MLA can be reduced using interpolation of the data acquired from adjacent transmitted beams-a method called synthetic transmit beamforming (STB). A recently proposed filtered delay-multiply-and-sum (F-DMAS) is a novel beamforming method, based on modified autocorrelation of the aperture data, which provides superior contrast resolution compared to the DAS beamforming. In this study, we demonstrate that a combination of the F-DMAS with the STB compensated MLA results in superior contrast as compared to both DAS beamformed STB and DAS beamformed single-line acquisition. Moreover, we propose a novel formulation for adaptive-lag F-DMAS that outperforms both DAS and F-DMAS in terms of contrast and lateral resolutions. The results are demonstrated in tissue-mimicking phantom and in human cardiac data.

Signal Coherence and Image Amplitude With the Filtered Delay Multiply and Sum Beamformer

The filtered delay multiply and sum (F-DMAS) beamformer has recently been presented in the context of medical ultrasound image formation. This nonlinear beamformer produces images with improved contrast resolution and noise rejection when compared with the delay and sum (DAS) beamformer. In an attempt to better understand the origin of the improved image quality, this paper shows a theoretical study of the image amplitude statistics backed up by numerical simulations. The results show that the difference in image amplitude using the DAS or F-DMAS beamformers can be partly explained by the way signal coherence influences both beamformers. When using the F-DMAS compared with the DAS beamformer, the image amplitude is shown to be more dependent on the signal coherence. Experimental ultrasound images of a phantom confirm our findings.

A Nonlinear Beamformer Based on p-th Root Compression—Application to Plane Wave Ultrasound Imaging

Ultrafast medical ultrasound imaging is necessary for 3D and 4D ultrasound imaging, and it can also achieve high temporal resolution (thousands of frames per second) for monitoring of transient biological phenomena. However, reaching such frame rates involves reduction of image quality compared with that obtained with conventional ultrasound imaging, since the latter requires each image line to be reconstructed separately with a thin ultrasonic focused beam. There are many techniques to simultaneously acquire several image lines, although at the expense of resolution and contrast, due to interference from echoes from the whole medium. In this paper, a nonlinear beamformer is applied to plane wave imaging to improve resolution and contrast of ultrasound images. The method consists of the introduction of nonlinear operations in the conventional delay-and-sum (DAS) beamforming algorithm. To recover the value of each pixel, the raw radiofrequency signals are first dynamically focused and summed on the plane wave dimension. Then, their amplitudes are compressed using the signed p t h root. After summing on the element dimension, the signed p-power is applied to restore the original dimensionality in volts. Finally, a band-pass filter is used to remove artificial harmonics introduced by these nonlinear operations. The proposed method is referred to as p-DAS, and it has been tested here on numerical and experimental data from the open access platform of the Plane wave Imaging Challenge in Medical UltraSound (PICMUS). This study demonstrates that p-DAS achieves better resolution and artifact rejection than the conventional DAS (for p = 2 with eleven plane wave imaging on experimental phantoms, the lateral resolution is improved by 21 % , and contrast ratio (CR) by 59 % ). However, like many coherence-based beamformers, it tends to distort the conventional speckle structure (contrast-to-noise-ratio (CNR) decreased by 45 % ). It is demonstrated that p-DAS, for p = 2 , is very similar to the nonlinear filtered-delay-multiply-and-sum (FDMAS) beamforming, but also that its impact on image quality can be tuned changing the value of p.

Spatial Coherence of Backscattered Signals in Multi-Line Transmit Ultrasound Imaging and Its Effect on Short-Lag Filtered-Delay Multiply and Sum Beamforming

In Multi-Line Transmission (MLT), high frame-rate ultrasound imaging is achieved by the simultaneous transmission of multiple focused beams along different directions, which unfortunately generates unwanted artifacts in the image due to inter-beam crosstalk. The Filtered-Delay Multiply and Sum (F-DMAS) beamformer, a non-linear spatial-coherence (SC)-based algorithm, was demonstrated to successfully reduce such artifacts, improving the spatial resolution at the same time. In this paper, we aim to provide further insights on the working principle and performance of F-DMAS beamforming in MLT imaging. First, we carry out an analytical study to analyze the behavior and trend of backscattered signals SC in MLT images, when the number of simultaneously transmitted beams and/or their angular spacing change. We then reconsider the F-DMAS algorithm proposing the “short-lag F-DMAS” formulation, in order to limit the maximum lag of signals used for the SC computation on which the beamformer is based. Therefore, we investigate in simulations how the performance of short-lag F-DMAS varies along with the maximum lag in the different MLT configurations considered. Finally, we establish a relation between the obtained results and the signals SC trend.