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Synthetic microwave focusing methods have been widely adopted in qualitative medical imaging to detect and localize anomalies based on their electromagnetic scattering signatures. This paper discusses the principles, challenges, and limitations of synthetic microwave-focusing techniques in medical applications. It is shown that the various focusing techniques, including time reversal, confocal imaging, and delay-and-sum, are all based on the scalar solution of the electromagnetic scattering problem, assuming the imaged object, i.e., the tissue or object, is linear, reciprocal, and time-invariant. They all aim to generate a qualitative image, revealing any strong scatterer within the imaged domain. The differences among these techniques lie only in the assumptions made to derive the solution and create an image of the relevant tissue or object. To get a fast solution using limited computational resources, those methods assume the tissue is homogeneous and non-dispersive, and thus, a simplified far-field Green's function is used. Some focusing methods compensate for dispersive effects and attenuation in lossy tissues. Other approaches replace the simplified Green's function with more representative functions. While these focusing techniques offer benefits like speed and low computational requirements, they face significant ongoing challenges in real-life applications due to their oversimplified linear solutions to the complex problem of non-linear medical microwave imaging. This paper discusses these challenges and potential solutions. [ABSTRACT FROM AUTHOR]

Synthetic microwave focusing methods have been widely adopted in qualitative medical imaging to detect and localize anomalies based on their electromagnetic scattering signatures. This paper discusses the principles, challenges, and limitations of synthetic microwave-focusing techniques in medical applications. It is shown that the various focusing techniques, including time reversal, confocal imaging, and delay-and-sum, are all based on the scalar solution of the electromagnetic scattering problem, assuming the imaged object, i.e., the tissue or object, is linear, reciprocal, and time-invariant. They all aim to generate a qualitative image, revealing any strong scatterer within the imaged domain. The differences among these techniques lie only in the assumptions made to derive the solution and create an image of the relevant tissue or object. To get a fast solution using limited computational resources, those methods assume the tissue is homogeneous and non-dispersive, and thus, a simplified far-field Green’s function is used. Some focusing methods compensate for dispersive effects and attenuation in lossy tissues. Other approaches replace the simplified Green’s function with more representative functions. While these focusing techniques offer benefits like speed and low computational requirements, they face significant ongoing challenges in real-life applications due to their oversimplified linear solutions to the complex problem of non-linear medical microwave imaging. This paper discusses these challenges and potential solutions.

In this article, an ultra‐wideband (UWB) monostatic radar based microwave imaging (MWI) approach is proposed to detect the presence and localize the position of breast tumor in women (usually greater than 45 years of age). For this purpose, a "C" shaped elliptically polarized DRA (dielectric resonator antenna) with an impedance bandwidth of 7.3 GHz (i.e., 3.4–10.7 GHz) covering the UWB has been proposed as a sensor to record the backscattered S parameter signals from the breast tissues. This is done by rotating the proposed DRA in monostatic radar configuration around the breast phantom with an interval of 30° in elevation (0–180) and azimuthal planes (0–360), respectively. The recorded "S" parameter data is then processed using beam‐forming algorithms namely delay and sum (DAS), improved delay and sum (IDAS), delay multiply and sum (DMAS) to form 2D images of the breast tumor and locate its position (using MATLAB R 2013a). The design and simulation of the entire set up that includes the C shaped UWB DRA & Bio media (breast phantom) is done using CST MWS V'17. The fabrication of the proposed DRA is carried out using wet etching and water jet cutting process. The physical model of the Bio media is prepared using gelatin (skin), petroleum‐jelly (fat), and wheat‐flour (tumor). The validation of antenna radiation parameters is done using a VNA (vector network analyzer) model no. E5063A and good agreement between the simulated and measured results is observed. The proposed C shaped DRA is used in a monostatic radar based configuration to collect "S" parameters and the data is processed in a GPU to reconstruct a 2D image of the scanned breast phantom area. The size and detected location of tumor using beam‐forming is also close to the actual physical location of tumor with an error of 6.2% from the actual tumor location. [ABSTRACT FROM AUTHOR]

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Ultrasound imaging is an important modality used in medical imaging. One of the significant stages in the ultrasound imaging is the beamforming process. This article proposes a new technique for reducing the overall computational time of adaptive linear ultrasound imaging. The method uses the discrete cosine transform‐based reconstruction for missing data imputation. The novelty of the paper is that we do not need to beam‐form the total scan lines, so the time of image construction can be saved significantly. In other words, a fraction of the total scan lines is selected for beamforming and the others are assumed to have values as Not‐a‐Number (NaN). The proposed reconstruction technique tries to assign appropriate values to the NaN ones. We applied the proposed method to the simulated and experimental radio frequency (RF) datasets for resolution and contrast evaluation. Results showed that the proposed technique is near to the minimum variance (MV) method in terms of resolution and contrast, and has less computational time for image formation compared to the MV. As some quantitative examples in some experiments we have formed only 50% and 33% of the total lines and reconstructed the rest, then we have been able to increase the frame rate twice and three times, respectively, which can be very useful in many applications, especially in echocardiography imaging. In addition, since the execution time of the reconstruction algorithm is not very significant, we were also able to increase the speed by two and three times while achieving an error of less than 10% compared to the case of using all image lines. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, a damage imaging method for 2-D concrete structures is proposed by employing embedded tubular piezoceramic transducers. The proposed method can image the damages when few numbers of transducers are used or less experimental data is collected. First, the time difference of arrival-based delay and sum (DAS) imaging method is adopted to improve the damage localization accuracy for concrete structural health monitoring. Compared with the conventional DAS imaging algorithm, the proposed method increases the potential number of combinations between the response signals induced by the damage in each transmitter and sensor pair, improving the signal to noise ratio of the imaging map and enhancing the performance of the defect detection and location. Second, to enable the proposed method applicable to a 2-D concrete structure (such as cement concrete pavement and shear walls), embeddable tubular lead zirconate titanate (PZT) transducers rather than conventional PZT patches are used. The new tubular PZT transducers are able to generate radially uniform stress waves in a planar concrete structure. Due to the special construction of the tubular PZT transducers, the detection aperture is significantly improved. Therefore, a few transducers are needed in contrast with the conventional PZT patches. The experimental results conducted on a concrete slab with eight embedded tubular PZT transducers demonstrate that the proposed method can predict the defect accurately and efficiently even with few transducers and less experimental data.

The paper aims at studying the vital factors affecting the beam pattern and analyzing the performance of Direction of Arrival (DOA) estimation algorithms. The information needed to calculate the DOA is obtained by analyzing the wave impinging on the linear array using MATLAB. The performance evaluation of the three directions of arrival estimation (DOA) algorithms namely Delay and Sum, Minimum Variance Distorsionless Response (MVDR) and MUSIC has been done in open space and closed room. Among the three, the MUSIC algorithm has the highest resolution however the need of large number of frames to maintain the accuracy, high computational demands and the number of sources present to be known beforehand are its major limitations. [ABSTRACT FROM AUTHOR]

Despite the promising clinical application of linear-array photoacoustic tomography, it has been shown the variable speed of sound would severely affect the photoacoustic imaging quality, resulting in the target deterioration and inaccurate depth positioning in the conventional constant speed assumed delay and sum (DAS) reconstruction. By contrast, multi-stencils fast marching (MSFM) method is able to produce accurate time delay map for the tissue with inhomogeneous acoustic speed. This study explored the combination of DAS reconstruction algorithm with the MSFM approach to reduce the imaging distortions due to the speed spatial variation, where the target structure and target position in depth could be measured more precisely. To validate the performance of the proposed method, numerical, phantom, and in vivo photoacoustic studies were conducted with the qualitative and quantitative analysis, especially in the detection of mouse deep brain tumor with an intact skull. [ABSTRACT FROM AUTHOR]

Guided-wave structural health monitoring (SHM) systems with piezoelectric sensors are investigated for localisation of barely visible impact damage in CFRP plates under vibration and different thermal conditions. A single baseline set is used in a delay-and-sum algorithm with temperature correction for damage localisation in a large temperature range. Damage localisation is also demonstrated under transient thermal conditions, with signals recorded while the temperature is rapidly decreased. Damage severity due to successive impact events is studied under constant temperature. Damage is also localised when the plate is subjected to random vibration. [ABSTRACT FROM AUTHOR]

Reconstruction of ultrasound data from single plane wave Radio Frequency (RF) data is a challenging task. The traditional Delay and Sum (DAS) method produces an image with low resolution and contrast, if employed with RF data from only a single plane wave. A Coherent Compounding (CC) method that reconstructs the image by coherently summing the individual DAS images was proposed to enhance the image quality. However, CC relies on a large number of plane waves to accurately sum the individual DAS images, hence it produces high quality images but with low frame rate that may not be suitable for time-demanding applications. Therefore, there is a need for a method that can create a high quality image with higher frame rates. Furthermore, the method needs to be robust against the input transmission angle of the plane wave. To reduce the method's dependence on the input angle, we propose to unify the RF data at different angles by learning a linear data transformation from different angled data to a common, 0 ° data. We further propose a cascade of two independent neural networks to reconstruct an image, similar in quality to CC, by making use of a single plane wave. The first network, denoted as "PixelNet", is a fully Convolutional Neural Network (CNN) which takes in the transformed time-delayed RF data as input. PixelNet learns optimal pixel weights that get element-wise multiplied with the single angle DAS image. The second network is a conditional Generative Adversarial Network (cGAN) which is used to further enhance the image quality. Our networks were trained on the publicly available PICMUS and CPWC datasets and evaluated on a completely separate, CUBDL dataset obtained from different acquisition settings than the training dataset. The results thus obtained on the testing dataset, demonstrate the networks' ability to generalize well on unseen data, with frame rates better than the CC method. This paves the way for applications that require high-quality images reconstructed at higher frame rates. • A linear data transformation method to unify RF data across different plane waves. • A two cascaded neural network was designed to be trained with low amounts of data. • Method shows high generalizability on test data not included in training. • Images similar to coherent compounding method are obtained at 5x higher frame rate. • Higher frame rate could be used in applications like functional ultrasound imaging. [ABSTRACT FROM AUTHOR]

Reconstruction of photoacoustic (PA) images acquired with clinical ultrasound transducers is usually performed using the Delay and Sum (DAS) beamforming algorithm. Recently, a variant of DAS, referred to as Delay Multiply and Sum (DMAS) beamforming has been shown to provide increased contrast, signal-to-noise ratio (SNR) and resolution in PA imaging. The main reasons for the use of DAS beamforming in photoacoustics are its simple implementation, real-time capability, and the linearity of the beamformed image to the PA signal. This is crucial for the identification of different chromophores in multispectral PA applications. In contrast, current DMAS implementations are not responsive to the full spectrum of sound frequencies from a photoacoustic source and have not been shown to provide a reconstruction linear to the PA signal. Furthermore, due to its increased computational complexity, DMAS has not been shown yet to work in real-time. Here, we present an open-source real-time variant of the DMAS algorithm, signed DMAS (sDMAS), that ensures linearity in the original PA signal response while providing the increased image quality of DMAS. We show the applicability of sDMAS for multispectral PA applications, in vitro and in vivo. The sDMAS and reference DAS algorithms were integrated in the open-source Medical Imaging Interaction Toolkit (MITK) and are available as real-time capable implementations.

Purpose: Ultrasound image quality is related to the receive beamformer's ability. Delay and sum (DAS), a conventional beamformer, is combined with the coherence factor (CF) technique to suppress side lobe levels. The purpose of this study is to improve these beamformer's abilities. Methods: It has been shown that extension of the receive aperture can improve the receive beamformer's ability in radar studies. This paper shows that the focusing quality of CF and CF+DAS in medical ultrasound can be increased by extension of the receive aperture's length in phased synthetic aperture (PSA) imaging. Results: The 3-dB width of the main lobe in the receive beam related to CF focusing decreased to 0.55 mm using the proposed PSA compared to the conventional phased array (PHA) imaging, whose FWHM is about 0.9 mm. The clutter-to-total-energy ratio (CTR) represented by R20 dB showed an improvement of 50 and 33% for CF and CF+DAS beamformers, respectively, with PSA as compared to PHA. In addition, simulation results validated the effectiveness of PSA versus PHA. Conclusion: In applications where there are no important limitations on the SNR, PSA imaging is recommended as it increases the ability of the receive beamformer for better focusing. [ABSTRACT FROM AUTHOR]

Dynamic receive beamforming on a Delta–Sigma modulator’s low-resolution output bit-stream suffers from a severely increased noise floor, rendering the promising method infeasible. This paper addresses the mechanism behind the increased noise floor. By using multirate theory and bifrequency analysis, we show that the increased noise floor is caused by aliasing/imaging of the powerful quantization noise from specific frequency regions according to the focus depth. We analyze both the conventional delay-and-sum method and the previously proposed insert zero compensation method. For the latter technique, we show that the alias/image bands have the first-order suppression because of a zero at the origin. This finding leads to the proposal of an architecture combining a cascaded integrator-comb filter with the insert zero compensation method. Backed by simulations of beamformed Delta–Sigma modulated sequences and point spread functions, we compare this architecture to different compensation methods and the ideal Delta–Sigma beamformer. The proposed technique is shown to have low implementation cost and achieve levels of dynamic range comparable to those of the ideal Delta–Sigma beamformer. [ABSTRACT FROM PUBLISHER]

Commercial ultrasonic phased array (PA) systems can perform multiple inspections in real-time using array transducers. This approach involves firing army elements in a particular sequence to produce high-resolution images at a high frame rate with excellent signal-to-noise ratio (SNR). Unfortunately, PA systems are complex and expensive. This study proposes a simpler, cheaper, non-real-time ultrasonic army system incorporating the total focusing method (TFM), and the performance of the proposed system is compared with that of a commercial PA system. Studying results shows that both systems have similar apparent axial resolution, but the apparent lateral resolution of the proposed system is far better than the L-scan but falls short in S-scan of a commercial PA system under a quiet testing environment. Moreover, the array performance indicator (API) values of TFM are lower than those of S-scan and L-scan, and the TFM has the highest SNR than the other methods. These results show that the performance of TFM array system is better than the commercial PA system, except for time consumption when switching the channels. Automatically switching the source and receiver channels could further the development of inexpensive, high-performance TFM arrays for ultrasonic nondestructive testing (NDT). It is anticipated that rapid advancements in electronic components, computer science, and digital signal processing will lead to improvements in near-real-time TFM array systems. [ABSTRACT FROM AUTHOR]

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, Δ x , in the lateral direction. Accordingly, the performance of FDMAS was evaluated in this study by fine-tuning Δ x 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 Δ x 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 Δ x 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 Δ x 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. [ABSTRACT FROM AUTHOR]

• Combination of tensor completion and STA is proposed to improve the frame rate. • In the proposed method, only a limited number of elements are excited for emission. • Tensor completion is used for optimizing image quality. • By using this technique, the STA runtime is reduced significantly. • Our results confirm a close image quality of the proposed method to the original STA. One of the most important methods in medical ultrasound imaging is the synthetic transmit aperture (STA). Despite the image quality improvement in the STA, this method suffers from several limitations, including a limited data acquisition rate and an increase in the overall time to form a single frame. Tensor completion (TC) is a powerful technique that uses rank minimization to recover missing information from a low-rank tensor. This paper provides a novel random synthetic transmit aperture (RSTA) method based on using only a randomly selected part (a fraction) of the linear array elements in the transmit mode to increase the data acquisition rate and then applying the tensor completion (TC) to improve the image quality. By the proposed method, as it is not necessary to transmit all elements sequentially, the data acquisition rate is improved and the overall time for creating an image is also significantly reduced. We investigated the proposed idea by using several simulated and experimental phantoms. Results showed that the proposed method could increase the data acquisition rate up to three times with the image quality difference of less than 6% compared to the original STA method. [ABSTRACT FROM AUTHOR]

Background: This paper presents an improved radar-based imaging system for breast cancer detection that features p-slot ultrawideband antennae in a 32-array set-up. The improved reconstruction algorithm incorporates the phase coherence factor (PCF) into the conventional delay and sum (DAS) beamforming algorithm, thus effectively suppressing noise arising from the side- and gratinglobe interferences., Methods: The system is tested by using several breast models fabricated from chemical mixtures formulated on the basis of realistic human tissues. Each model is placed in a hemispherical breast radome that was fabricated from polylactide material and surrounded by 32 p-slot antennae mounted in four concentric layers. These antennae are connected to an 8.5 GHz vector network analyser through two 16-channel multiplexers that automatically switch different combinations of transmitter and receiver pairs in a sequential manner., Results: The system can accurately detect 5 mm tumours in a complex and homogeneously dense 3D breast model with an average signal-to-clutter ratio and full-width half-maximum of 7.0 dB and 2.3 mm, respectively. These values are more competitive than the values of other beamforming algorithms, even with contrasts as low as 1:2., Conclusion: The proposed PCF-weighted DAS is the best-performing algorithm amongst the tested beamforming techniques. This research paves the way for a clinical trial involving human subjects. Our laboratory is planning such a trial as part of future work., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)