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This study's primary goal is to improve the accuracy and efficiency of acoustic wave propagation simulations using circular probe models in ultrasonography. This research aims to develop a detailed understanding of how variations in boundary conditions and wave characteristics influence the fidelity of ultrasound imaging. A range of simulation techniques were employed, focusing on non-dispersive and dispersive scenarios, to model acoustic wave behavior comprehensively. The study utilized Gaussian beamforming techniques and improved kernel functions to refine the resolution and decrease computational overhead. Various scenarios were simulated to analyze the impact of wave scattering and dispersion on imaging outcomes. The simulations demonstrated significant improvements in image resolution and accuracy. The refined methods allowed for more apparent distinctions in wave behavior under different boundary conditions, providing deeper insights into wave propagation dynamics. The results confirmed that controlling dispersion and scattering is critical for enhancing imaging quality. This research contributes to the field of ultrasonic imaging by presenting advanced simulation methods that offer more accurate and efficient imaging solutions. The study provides valuable insights into optimizing ultrasonic probes and imaging techniques by focusing on the impact of wave characteristics and boundary conditions. The findings have significant implications for medical diagnostics and material characterization, suggesting potential improvements in ultrasound technology for better patient outcomes and more precise material assessments.

The article discusses the design of advanced embedded algorithms that aim to manage and control the measurement process using the Electrical Impedance Tomography and Ultrasonic Tomography methods. The project aims to develop solutions that optimize the performance of embedded devices that must operate on limited resources such as memory, computing power, or bandwidth. Minimizing energy consumption is an important aspect, especially for battery-powered devices. Algorithms must also be adapted to specific hardware constraints, such as low RAM or CPU limitations, which require complex engineering and optimization. Additionally, the project assumes the implementation of algorithms that consider security aspects, which is crucial in protecting data processed and transmitted by the device. It also requires the development of effective communication methods between the embedded device and other systems, including appropriate communication protocols.

Metallurgical defects in metal laser additive manufacturing (LAM) are inevitable due to complex non-equilibrium thermodynamics. A laser ultrasonic system was designed for detecting surface/near-surface defects in the layer-by-layer LAM process. An approach was proposed for ultrasonic imaging of defects based on variable time window intensity mapping with adaptive 2σ threshold denoising. The Gaussian mixture model hypothesis and expectation-maximization algorithm can automatically differentiate between components dominated by defects and background noises, thereby providing an adaptive threshold that accommodates detection environments and surface roughness levels. Results show that the ultrasonic wave reflection at defect boundaries diminishes far-field ultrasonic intensity upon pulsed laser irradiation on surface defects, enabling defect size and location characterization. This method is applicable to LAM samples with a significant surface roughness of up to 37.5 μm. It can detect superficial and near-surface defects down to 0.5 mm in diameter and depth, making it significant for online defect detection in additive manufacturing.

2D and 3D ultrasonic imaging has so far not been demonstrated in pure molten lead in the open literature. In this study the development of such an ultrasonic device for imaging is outlined and results from testing at 380 °C in lead are presented. The main difficulties were found to be achieving then maintaining suitable wetting while ensuring suitable durability of the device, both due to the harsh nature of molten lead and the elevated temperatures. The successful detection and imaging (2D and 3D), of differently shaped targets, where the features were above the size of the transmitted ultrasound beam was demonstrated.

This paper presented a new approach for noncontact inspection of defects in milling groove brazed joints of thrust chamber with laser ultrasonic testing method and synthetic aperture focusing technique (SAFT). Firstly, laser ultrasonic testing methods for milling groove brazed joints of thrust chamber was studied. Subsequently, numerical models were constructed to analyze the influence of defects on laser-excited signals. The analysis revealed that the brazed defects caused internal waves to reflect on the rib surface, manifesting as defect echo signals preceding the outer wall echo. Through scanning setting, the obtained SAFT images illustrate the presence of the defect directly and clearly. Furthermore, an experimental system was established to detect and image artificial defects with different degrees of weld leakage. The experimental results are consistent with simulation results, validating the capability and effectiveness of the testing and imaging method. In general, the proposed laser ultrasound method offers inherent advantages of non-contact detection with high resolution and precision, and it is easy to achieve fast and automated scanning of large and complex structures like thrust chambers, demonstrating its potential for enhancing the safety and reliability of liquid rocket engines.

Abstract The accurate segmentation of breast tumours is important for the diagnosis and treatment of breast cancer. When using the classic U‐Net, Attention‐UNet, and UNet++ to segment the tumour, there are problems of oversegmentation, incorrect segmentation, and poor edge continuity. In this paper, an effective tumour segmentation method, EfficientUNet, is proposed. EfficientUNet adopts a step‐by‐step enhancement method, combining ResNet18, a channel attention mechanism and deep supervision. ResNet18, as the encoder of the whole network, solves the problem of gradient disappearanceand improves the feature extraction ability of the model. The channel attention module makes the model more accurate in tumour edge processing. The deep supervision technology accelerates the model training and provides the convergence direction for the model. In addition, it is found that when adjusting the size of the image, the method of image filling before clipping (or zooming) is more conducive to model learning than the direct interpolation method. And a comparative experiment wasperformed on dataset B. Compared to U‐Net, Attention‐UNet and UNet++, EfficientUNet has the highest performance. Finally, the ablation experiment also indicated the effectiveness of each module in EfficientUNet.

In this work, we investigate the localization of point-like targets in the presence of multiple scattering. We focus on the often omitted scenario in which measurement data is affected by multiple scattering, and a simpler model is employed in the estimation. We study the impact of such model mismatch by means of the Misspecified Cramér-Rao Bound (MCRB). In numerical simulations inspired by tomographic inspection in Ultrasound Nondestructive Testing (UNDT), the MCRB is shown to correctly describe the estimation variance of localization parameters under misspecification of the wave propagation model. We provide extensive discussion on the utility of the MCRB in the practical task of verifying whether a chosen misspecified model is suitable for localization based on the properties of the maximum likelihood estimator and the nuanced distinction between bias and parameter space differences. Finally, we highlight that careful interpretation is needed whenever employing the classical CRB in the presence of mismatch through numerical examples based on the Born approximation and other simplified propagation models stemming from it. Although motivated by UNDT, the analysis and discussion throughout this work generally apply to localization tasks based on scalar wave field measurements.

Distance sensors are important for mobile robots to perceive surrounding environment. Typical sensors like LiDARs and depth cameras have been widely used, yet each has its limitations, such as LiDARs’ relatively high cost, depth cameras’ limitation to indoor use, and their poor performance in detecting transparent objects directly. On the other hand, ultrasonic phased array that integrates multiple ultrasonic sensors not only enables 3D ranging and imaging, but also provides advantages of strong environmental adaptability, being cost-effective and being able to detect transparent objects. To explore the application of in-air ultrasonic phased arrays for mobile robots, we simulate a 40 kHz $5\times 5$ non-uniform sparse ultrasonic phased array. The simulator emulates the process of phased array transmission and reception, and utilizes algorithms such as beamforming and matched filtering to obtain depth information in three-dimensional space. Then, a multi-view indoor 3D reconstruction method fusing the ultrasonic phased array and a monocular camera is proposed, where two scanning strategies are developed to handle different scenarios. Finally, the method is validated in different Gazebo scenarios and compared with other baseline methods like LiDARs and depth cameras. The experimental results reveal the method’s strong performance in terms of accuracy, consistency and completeness.

Extracting head waves and subsequently uploading their results from the downhole to the surface system in real time could improve the real-time guidance of ultrasonic imaging logging while drilling (UILWD) for drilling operations. To realize the downhole real-time extraction of head waves in this logging, three aspects were explored in this study. First, an improved energy ratio head-wave arrival extraction algorithm based on the weighting coefficients and characteristic functions, along with an amplitude detection method relying on peak-to-peak values, was proposed. Second, an echo reception pre-processing analog circuit and a digital signal processing circuit based on FPGA were designed. A pipeline algorithm was developed in FPGA to extract the arrival time and amplitude of the head wave. Finally, software simulations, laboratory tests, and field experiments related to this method were conducted. Our results showed that the real-time head-wave extraction method demonstrated a strong anti-noise ability in real time. The maximum relative error of the arrival time was less than 5%. The relative error of the amplitude was acceptable, and 90% of this value was within 5%. Through the measurement, the time of processing a single-channel waveform by a downhole algorithm was less than 15 ms, thus meeting the requirements for the real-time processing of downholes.

Rui Wang,1,* Yijing Yao,1,2,* Yihui Gao,1 Mengyao Liu,1 Qian Yu,3 Xuejiao Song,4 Xiao Han,5 Dechao Niu,6 Lixin Jiang1,2 1Department of Ultrasound, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200127, People’s Republic of China; 2Shanghai Institute of Ultrasound in Medicine, Shanghai, 200233, People’s Republic of China; 3Department of Ultrasonography, Shanghai Jiao Tong University Affiliated No. 6 Hospital, Shanghai, 200233, People’s Republic of China; 4School of Physical and Mathematical Sciences, Nanjing Tech University (NanjingTech), Nanjing, 211800, People’s Republic of China; 5Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, Jiangsu, 215123, People’s Republic of China; 6Lab of Low-Dimensional Materials Chemistry, Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai, 200237, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lixin Jiang; Dechao Niu, Email jinger_28@sina.com; dcniu@ecust.edu.cnBackground: Pancreatic cancer is regarded as one of the most lethal types of tumor in the world, and optional way to treat the tumor are urgently needed. Cancer stem cells (CSCs) play a key role in the occurrence and development of pancreatic tumors. CD133 is a specific antigen for targeting the pancreatic CSCs subpopulation. Previous studies have shown that CSC-targeted therapy is effective in inhibiting tumorigenesis and transmission. However, CD133 targeted therapy combined with HIFU for pancreatic cancer is absent.Purpose: To improve therapeutic efficiency and minimize side effects, we carry a potent combination of CSCs antibody with synergist by an effective and visualized delivery nanocarrier to pancreatic cancer.Materials and Methods: Multifunctional CD133-targeted nanovesicles (CD133-grafted Cy5.5/PFOB@P-HVs) with encapsulated perfluorooctyl bromide (PFOB) in a 3-mercaptopropyltrimethoxysilane (MPTMS) shell modified with poly ethylene glycol (PEG) and superficially modified with CD133 and Cy 5.5 were constructed following the prescribed order. The nanovesicles were characterized for the biological and chemical characteristics feature. We explored the specific targeting capacity in vitro and the therapeutic effect in vivo.Results: The in vitro targeting experiment and in vivo FL and ultrasonic experiments showed the aggregation of CD133-grafted Cy5.5/PFOB@P-HVs around CSCs. In vivo FL imaging experiments demonstrated that the nanovesicles assemble for the highest concentration in the tumor at 24 h after administration. Under HIFU irradiation, the synergistic efficacy of the combination of the CD133-targeting carrier and HIFU for tumor treatment was obvious.Conclusion: CD133-grafted Cy5.5/PFOB@P-HVs combined with HIFU irradiation could enhance the tumor treatment effect not only by improving the delivery of nanovesicles but also by enhancing the HIFU thermal and mechanical effects in the tumor microenvironment, which is a highly effective targeted therapy for treating pancreatic cancer.Keywords: multifunctional nanovesicles, cancer stem cells, high-intensity focused ultrasound, in vivo fluorescent imaging, ultrasonic imaging

Corrosion is one of the critical factors leading to the failure of steel structures. Ultrasonic C-scans are widely used to identify corrosion damage. Limited by the range of C-scans, multiple C-scans are usually required to cover the whole component. Thus, stitching multiple C-scans into a panoramic image of the area under detection is necessary for interpreting non-destructive testing (NDT) data. In this paper, an image mosaic method for ultrasonic C-scan based on scale invariant feature transform (SIFT) is proposed. Firstly, to improve the success rate of registration, the difference in the probe starting position in two scans is used to filter the matching pairs of feature points obtained by SIFT. Secondly, dynamic programming methods are used to search for the optimal seam path. Finally, the pixels in the overlapping area are fused by fade-in and fade-out fusion along the seam line. The improved method has a higher success rate of registration and lower image distortion than the conventional method in the mosaic of ultrasonic C-scan images. Experimental results show that the proposed method can stitch multiple C-scan images of a testing block containing artificial defects into a panorama image effectively.

The total focusing method (TFM) is often considered to be the ‘gold standard’ for ultrasonic imaging in the field of nondestructive testing. The use of matrix phased arrays as probes allows for high-resolution volumetric TFM imaging. Conventional TFM imaging involves the use of full matrix capture (FMC) for ultrasonic signals acquisition, but in the case of a matrix phased array, this approach is associated with a huge volume of data to be acquired and processed. This severely limits the frame rate of volumetric imaging with 2D probes and necessitates the use of high-end equipment. Thus, the aim of this research was to develop a novel design method for determining the optimal sparse 2D probe configuration for specific conditions of ultrasonic imaging. The developed approach is based on simulated annealing and involves implementing the solution of the sparse matrix phased array layout optimization problem. In order to implement simulated annealing for the aforementioned task, its parameters were set, the acceptance function was introduced, and the approaches were proposed to compute beam directivity diagrams of sparse matrix phased arrays in TFM imaging. Experimental studies have shown that the proposed approach provides high-quality volumetric imaging with a decrease in data volume of up to 84% compared to that obtained using the FMC data acquisition method.

Abstract In this Letter, the authors present a novel imaging algorithm for multireceiver synthetic aperture sonar (SAS). The Loffeld's bistatic formula (LBF) including quasi‐monostatic (QM) and multireceiver deformation (MD) phases is first reformulated into range‐variant and range‐invariant phases. After compensating the range‐invariant phase, the subsequent steps are the extended Stolt mapping for each bistatic SAS. Based on simulations, the presented method can also provide high‐resolution result which is similar to that of back projection (BP) algorithm.

Based on a synthesized laser ultrasonic array, full matrix capture can be used to acquire data, which can then be post-processed using the total focusing method. However, this noncontact ultrasonic imaging technique has not been widely used because of the numerous artifacts in ultrasonic images and time-consuming data acquisition. To address these issues, this study proposes a post-processing algorithm, which uses the laser ultrasound directivity information to suppress the artifacts in the total focusing method’s images. In particular, a weight factor is defined using the directivity information. By multiplying the image intensity of the total focusing method with this factor, the algorithm uses not only the amplitude and phase information of laser ultrasound but also its directivity information. The experimental results indicate that four types of artifacts are suppressed. Because the grating lobe artifacts can be suppressed, a larger element spacing can be used to reduce the data acquisition time.

Abstract The authors present a low‐power area‐efficient subarray beamforming receiver (RX) structure for a miniaturized 3‐D ultrasound imaging system. Given that the delay‐and‐sum (DAS) and digitization functions consume most of the area and power in the receiver, the beamforming successive approximation register (SAR) analog‐to‐digital converter (ADC) shares its capacitive digital‐to‐analog converter (CDAC) with the delay cells. As a result, the delay cells implemented with capacitors are embedded in the CDAC with significant area reduction, further eliminating the need for power‐hungry ADC buffers. Furthermore, the dual reference 10‐bit SAR ADC reduces the area of CDAC by 32 times, achieving a switching energy reduction of 98.3%, compared to the conventional SAR ADC. As a result, the proposed beamforming SAR ADC, simulated using a 0.18 μm CMOS process, consumes 230 μW per channel, significantly reducing the per channel capacitance.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the formation of new vessels, synovial proliferation and destruction of articular cartilage. However, characteristic early diagnostic and therapeutic monitoring methods are still lacking. We report a study using a photoacoustic/ultrasound (PA/US) dual-mode imaging for RA disease. By establishing a collagen-induced (CIA) RA mouse model to classify disease states based on a subjective grading system, PA/US imaging allows real-time assessment of synovial erosion and vascular opacification within the knee joint in different disease states at high spatial resolution. The system also quantitatively monitors subcutaneous vascular physiology and morphology in the hind paw of mice, measuring the area and photoacoustic signal intensity of vascular proliferation and showing a positive correlation with disease grading. Compared to traditional subjective scoring of arthritis severity, the PA/US imaging is more sensitive i.e., vascular signals and synovial erosion can be observed early in the course of arthritis.

Additive manufacturing (AM) is an emerging technique for efficient fabrication of individually tailored and complex geometry parts. The fabrication process is prone to induce various defects that can have detrimental effects on the AM components. Therefore, a reliable technique that enables monitoring the integrity of AM components and in return helping to optimize the fabrication parameters in mission-critical structures is highly demanded. This work presents a fast and high-resolution damage visualization method using laser-ultrasonic (LU) imaging technique for accurately detecting and quantifying the subsurface defects in printed AM components. Specifically, a fully noncontact LU scanning system is implemented to generate and detect high signal-to-noise ratio laser ultrasonic waves using a pulsed laser and laser Doppler vibrometer, respectively. A strategy for fast defect localization using Rayleigh waves with circular scans is firstly proposed. The high-resolution 3D synthetic aperture focusing technique (SAFT) imaging with raster scans is subsequently performed focusing around the located damage areas to stereoscopically visualize and quantify the subsurface defects. The reconstructed images are further processed and improved using Gaussian filter algorithm to obtain accurate defect shapes, sizes, and positions. The feasibility of the proposed method is eventually verified on AlSi10Mg and stainless steel (316L) components containing subsurface defects with various types and dimensions. The measured sizes are well consistent with the designed values, suggesting that it is a reliable inspection method for AM parts to ensure quality control and feedback.

Abstract Background The non-invasive quantitative evaluation of left ventricle (LV) function plays a critical role in clinical cardiology. This study proposes a novel ultrasonic biomechanics method by integrating both LV vortex and wall motion to fully assess and understand the LV structure and function. The purpose of this study was to validate the ultrasonic biomechanics method as a quantifiable approach to evaluate LV function. Methods Firstly, B-mode ultrasound images were acquired and processed, which were utilized to implement parameters for quantifying the LV vortex and wall motion respectively. Next, the parameters were compared in polyvinyl alcohol cryogen (PVA) phantoms with different degree of stiffness corresponding to different freezing and thawing cycles in vitro. Finally, the parameters were computed in vivo during one cardiac cycle to assess the LV function in normal and abnormal subjects in vivo. Results In vitro study, the velocity field of PVA phantom differed with stiffness (varied elasticity modulus). The peak of strain for wall motion decreases with the increase of elasticity modulus, and periodically changed values. Statistical analysis for parameters of vortex dynamics (energy dissipation index, DI; kinetic energy fluctuations, KEF; relative strength, RS; and vorticity, W) based on different elasticity (E) of phantom depicted the good viability of this algorithm. In vivo study, the results confirmed that subjects with LV dysfunction had lower vorticity and strain (S) compared to the normal group. Conclusion Ultrasonic biomechanics method can obtain the vortex and wall motion of left ventricle. The method may have potential clinical value in evaluation of LV dysfunction.

Aims: This study explored the advantages and limitations of novel series of three-dimensional (3D) echocardiographic techniques and summarized their application methods for congenital heart diseases (CHDs).Method and result: Two-dimensional (2D), traditional 3D echocardiography, and TrueVue plus light and/or Glass novel 3D technologies were performed on 62 patients with CHD, and a clinical survey was designed to judge whether the novel 3D images were more helpful for understanding the cardiac condition and guide treatment than traditional 3D images. TrueVue increased the visual resolution and simulated the true texture of cardiac tissue, significantly improving the display ability of abnormal anatomical structures in CHDs. TrueVue Glass displayed the blood channel and the internal structure of cardiac cavity more intuitively, indicating a new observation aspect not shown by conventional echocardiography. The clinical survey results showed that the new 3D imaging methods effectively increased the diagnostic confidence of echocardiographers, enabled surgeons to better understand the details of lesions, promoted efficient communication, and improved the confidence of both doctors and patients in treatment.Conclusion: The combined application of TrueVue, TrueVue Light, and TrueVue Glass more closely simulated real anatomical features, showed more comprehensive and subtle blood flow in the lumen, not only increased the visual effect but also provided more useful diagnostic information, improved the accuracy of evaluation and treatment of CHD when compared to traditional imaging techniques, indicating that this combined application has significant clinical value.

The basic principle of ultrasound is to relate the time of flight of a received echo to the location of a reflector, assuming a known and constant velocity of sound. This assumption breaks down in austenitic welds, in which a microstructure with large oriented austenitic grains induces local velocity differences resulting in deviations of the ultrasonic beam. The inspection problem is further complicated by scattering at grain boundaries, which introduces structural noise and attenuation. Embedding material information into imaging algorithms usually improves image quality and aids interpretation. Imaging algorithms can take the weld structure into account if it is known. The usual way to obtain such information is by metallurgical analysis of slices of a representative mock-up fabricated using the same materials and welding procedures as in the actual component. A non-destructive alternative to predict the weld structure is based on the record of the welding procedure, using either phenomenological models or the finite element method. The latter requires detailed modelling of the welding process to capture the weld pool and the microstructure formation. Several parameters are at play, and uncertainties intrinsically affect the process owing to the limited information available. This paper reports a case study aiming to determine the most critical parameters and levels of complexity of the weld formation models from the perspective of ultrasonic imaging. By combining state-of-the-art welding simulation with time-domain finite element prediction of ultrasound in complex welds, we assess the impact of the modelling choices on the offset and spatial spreading of defect signatures. The novelty of this work is in linking welding simulation with ultrasonic imaging and quantifying the effect of the common assumptions in solidification modelling from the non-destructive examination perspective. Both aspects have not been explored in the literature to date since solidification modelling has not been used to support ultrasonic inspection extensively. The results suggest that capturing electrode tilt, welding power, and weld path correctly is less significant. Bead shape was identified as having the greatest influence on delay laws used to compute ultrasonic images. Most importantly, we show that neglecting mechanical deformation in FE, allowing for simpler thermal simulation supplemented with a phenomenological grain growth loop, does not reduce the quality of the images considerably. Our results offer a pragmatic balance between the complexity of the model and the quality of ultrasonic images and suggest a perspective on how weld formation modelling may serve inspections and guide pragmatic implementation.

Ultrasonography is an extensively used medical imaging technique for multiple reasons. It works on the basic theory of echoes from the tissues under consideration. However, the occurrence of signal dependent noise such as speckle destroys utility of ultrasound images. Speckle noise is subject to the composition of image tissue and parameters of image. It reduces the effectiveness of many image processing steps and decreases human perception of fine details form ultrasound images. In many medical image processing methods, despeckling is used as the preprocessing step before segmentation and feature extraction. Many speckle reduction filters are proposed but while combining many techniques some speckle diagnostic information should be preserved. Removal of speckle noise from ultrasound image by preserving edges and added features is a great challenging task in ultrasound image restoration. This paper aims at a comprehensive description and comparison of reduction of speckle noise of ultrasound fibroid image. Many filters are applied on ultrasound scanned images and the performance is marked in terms of some statistical measures. Even though several despeckling filters are there for speckle reduction, all are not good for ultrasound scanned images. A comparison of quality measures such as mean square error, peak signal-to-noise ratio, and signal-to-noise ratio is done in ultrasound images in despeckling.

Increasing number of lung diseases, unfavorable environmental factors, dissemination of infectious agents in a patient's body result in increased frequency of purulent-septic complications, thereby making the study on methods of their diagnosis and treatment relevant. Aim of the work: to examine the diagnostic value of lung ultrasound (US) and spiral computed tomography (SCT) in the diagnosis of acute abscesses and in determining the tactics of surgical treatment. Materials and methods. A prospective study of 40 cases of acute lung abscesses with diagnostic value of US and SCT examination to choose a surgical method in accordance with the type of acute lung abscess. Results. Male was dominated in the study (82.5 %). The median age was 52 (43.5; 60.0) years. SCT revealed an abscess with sequestration in 9 (22.5 %) of 40 patients, which was confirmed during surgery. A false negative result was obtained in 5 (35.7 %) patients out of 14. Lung US revealed sequestration in 14 (35.0 %) patients: 2 (14.3 %) of them were false positive. Transthoracic drainage was performed in 24 (92.3 %) of 26 patients without sequestration. In 2 (7.7 %) cases – video abscessoscopy (VAS). The median length of hospital stay was 34.5 (29.0; 43.0) days for patients without sequestration and 32.0 (26.0; 35.0) – with sequestration, Р = 0.16. Conclusions. Modern radiation imaging is an effective tool for the diagnosis of lung abscess. The sensitivity and specificity of computed tomography was 64.3 % and 100.0 %, sonography – 85.7 % and 92.3 %, respectively, in the study. The concurrent use of these diagnostic methods increases their information content: sensitivity up to 100.0 %, specificity up to 92.3 %. Video abscessoscopy with sequestrectomy is an effective method of treatment and etiological diagnosis of the process, which allows achieving the length of hospital stay comparable to patients without sequestration: 32.0 (26.0; 35.0) vs 34.5 (29.0; 43.0), Р = 0.16.

The article describes the progress of construction and research works on ultrasound tomography. The devices allow for non-invasive measurements of various objects using ultrasonic low and high-frequency transducers. The first constructions were made in a dispersed system with active measurement probes using 40 kHz converters. The next constructions were centralized into one measurement system where the measurement probes were connected separately. As a result, the measuring range of the supported ultrasonic transducers with 300 kHz, 400 kHz and 1 MHz has been extended. Apart from transmission and reflection tomography, the latest designs allow for controlling the ultrasound beam (beamforming) and support transducers up to 5 MHz.

This paper introduces an extended non-stationary phase-shift migration (ENSPS) method for ultrasound imaging of irregular surface components. This method extends non-stationary phase-shift (NSPS) technology based on the classical B-scan data to full-matrix capture (FMC) data. In addition, a new surface estimation method (SEM) is also proposed to prepare for ultrasonic imaging of irregular surface components. The method is implemented in the frequency domain, thereby ensuring the computational efficiency. In the numerical simulation, two components with different surface shapes were simulated to study the imaging ability of the method for hole defects and upper surface crack defects in irregular surface components. The simulation results show that the proposed ENSPS can detect hole defects with an interval of 0.5 mm and vertical surface cracks. In order to verify the simulation results, we set up a water-immersed ultrasonic experiment platform and obtained the ENSPS images. As a comparison, the extended phase-shift-plus-interpolation method (EPSPI) is also used to process the same data. The comparison results show that the algorithm proposed in this paper has the advantages of high resolution and low noise for the ultrasonic imaging of irregular surface components.

Muscle fasciculations, resulting from the spontaneous activation of motor neurons, may be associated with neurological disorders, and are often assessed with intramuscular electromyography (EMG). Recently, however, both ultrasound (US) imaging and multichannel surface EMG have been shown to be more sensitive to fasciculations. In this study we combined these two techniques to compare their detection sensitivity to fasciculations occurring in different muscle regions and to investigate the effect of EMG electrodes’ configuration on their agreement. Monopolar surface EMGs were collected from medial gastrocnemius and soleus with an array of 32 electrodes (10 mm Inter-Electrode Distance, IED) simultaneously with b-mode US images detected alongside either proximal, central or distal electrodes groups. Fasciculation potentials (FP) were identified from single differential EMGs with 10 mm (SD1), 20 mm (SD2) and 30 mm (SD3) IEDs, and fasciculation events (FE) from US image sequences. The number, location, and size of FEs and FPs in 10 healthy participants were analyzed. Overall, the two techniques showed similar sensitivities to muscle fasciculations. US was equally sensitive to FE occurring in the proximal and distal calf regions, while the number of FP revealed by EMG increased significantly with the IED and was larger distally, where the depth of FE decreased. The agreement between the two techniques was relatively low, with a percentage of fasciculation classified as common ranging from 22% for the smallest IED to 68% for the largest IED. The relevant number of events uniquely detected by the two techniques is discussed in terms of different spatial sensitivities of EMG and US, which suggest that a combination of US-EMG is likely to maximise the sensitivity to muscle fasciculations.

In order to study the development characteristics and formation location of mining overburden in thick coal seam under thick sandstone, the overburden movement caused by mining of thick coal seam at 2301 working face in a Datong mine is taken as an example. Theoretical calculation formula ultrasonic imaging and color drilling television system are used to calculate and quantitatively detect the development position of overburden strata in mining thick coal seam under thick sandstone. The results show that there are several sub-key layers in the overlying strata of coal seam, but there is only one main key layer, the abscission layer is mainly generated under each key layer, and the upward development height ends at the main key layer. the development depth of the abscission layer under the giant thick sandstone is respectively 343, 346.5, 328.61 m. It is proved that the stratum separation will be formed in the mining of the thick coal seam under the huge thick sandstone.

Various medical procedures make use of magnetic nanoparticles, such as Magnetic Drug Targeting (MDT), which boosts the demand for imaging modalities that are capable of in vivo visualizing this kind of particles. Magnetomotive Ultrasound is an imaging technique that can detect tissue, which is perfused by magnetic nanoparticles. In this contribution, we investigate the suitability of Magnetomotive Ultrasound to serve as a monitoring system during MDT. With the conducted measurements, it was possible for the first time to observe in vivo the accumulation of iron-oxide nanoparticles during a Magnetic Drug Targeting cancer treatment applied to a small animal (rabbit).

The grading evaluation of metacarpophalangeal rheumatoid arthritis (RA) ultrasonic images is a diagnostic challenge that heavily relies on the expertise of trained sonographers. This study presents a grading method for detecting and estimating the geometric and texture features of synovium thickening and bone erosion. Unlike previous studies in this area, this work uses the metrics and texture features of region of interest (ROI). The highlighted feature of metacarpophalangeal bone and the dark feature of the synovial thickening are extracted simultaneously by the segmented method based on the Gaussian scale space. The segmented results are analyzed to extract three quantitative geometric parameters, which are combined with gray-level co-occurrence matrix (GLCM) statistic texture features to describe the ultrasonic image of metacarpophalangeal RA. To obtain the preferable ability of classification, we applied a support vector machine (SVM) and various feature descriptors, including GLCM, local binary patterns (LBP), and GLCM + LBP, to grade the ultrasonic image of metacarpophalangeal RA. Results show that the SVM, based on our feature descriptor, provides the highest accuracy of up to 92.50%, of the four descriptors. The SVM based on GLCM+LBP descriptor shows better accuracy (86.55%) than either SVM + LBP (85.43%) or SVM+GLCM (82.51%) for discriminating among four grade RA ultrasonic images. Overall, this methodology points to a significant grading of metacarpophalangeal RA ultrasound images without medical expert analysis or blood sample analysis, such as detecting C-reactive protein, measuring erythrocyte sedimentation rate, and testing rheumatoid factor.

The central nervous system coordinates movement through forces generated by motor units (MUs) in skeletal muscles. To analyze MUs function is essential in sports, rehabilitation medicine applications, and neuromuscular diagnostics. The MUs and their function are studied using electromyography. Typically, these methods study only a small muscle volume (1 mm3) or only a superficial ( $4\times 4$ cm, cross-sectional) under voluntary contractions by ultrafast ultrasound imaging and spatiotemporal decomposition. We evaluate the performance of the method by simulation of active MUs’ mechanical response under weak contractions. We further test the experimental feasibility on eight healthy subjects. We show the existence of mechanical units that contribute to the tissue dynamics in the biceps brachii at low force levels and that these units are similar to MUs described by electromyography with respect to the number of units, territory sizes, and firing rates. This study introduces a new potential neuromuscular functional imaging method, which could be used to study a variety of questions on muscle physiology that previously were difficult or not possible to address.

As the Coronavirus Disease 2019 (COVID-19) continues to impact many aspects of life and the global healthcare systems, the adoption of rapid and effective screening methods to prevent the further spread of the virus and lessen the burden on healthcare providers is a necessity. As a cheap and widely accessible medical image modality, point-of-care ultrasound (POCUS) imaging allows radiologists to identify symptoms and assess severity through visual inspection of the chest ultrasound images. Combined with the recent advancements in computer science, applications of deep learning techniques in medical image analysis have shown promising results, demonstrating that artificial intelligence-based solutions can accelerate the diagnosis of COVID-19 and lower the burden on healthcare professionals. However, the lack of large, well annotated datasets poses a challenge in developing effective deep neural networks, especially in the case of rare diseases and new pandemics. To address this issue, we present COVID-Net USPro, an explainable few-shot deep prototypical network that is designed to detect COVID-19 cases from very few ultrasound images. Through intensive quantitative and qualitative assessments, the network not only demonstrates high performance in identifying COVID-19 positive cases, using an explainability component, but it is also shown that the network makes decisions based on the actual representative patterns of the disease. Specifically, COVID-Net USPro achieves 99.55% overall accuracy, 99.93% recall, and 99.83% precision for COVID-19-positive cases when trained with only five shots. In addition to the quantitative performance assessment, our contributing clinician with extensive experience in POCUS interpretation verified the analytic pipeline and results, ensuring that the network’s decisions are based on clinically relevant image patterns integral to COVID-19 diagnosis. We believe that network explainability and clinical validation are integral components for the successful adoption of deep learning in the medical field. As part of the COVID-Net initiative, and to promote reproducibility and foster further innovation, the network is open-sourced and available to the public.

Ultrasonic imaging logging can visually identify the location, shape, dip angle and orientation of fractures and holes. The method has not been effectively applied in the field; one of the prime reasons is that the results of physical simulation experiments are insufficient. The physical simulation of fracture and hole response in the laboratory can provide a reference for the identification and evaluation of the underground geological structure. In this work, ultrasonic scanning experiments are conducted on a grooved sandstone plate and a simulated borehole and the influence of different fractures and holes on ultrasonic pulse echo is studied. Experimental results show that the combination of ultrasonic echo amplitude imaging and arrival time imaging can be used to identify the fracture location, width, depth and orientation, along with accurately calculating the fracture dip angle. The evaluated fracture parameters are similar to those in the physical simulation model. The identification accuracy of the ultrasonic measurement is related to the diameter of the radiation beam of the ultrasonic transducer. A single fracture with width larger than or equal to the radiation beam diameter of the ultrasonic transducer and multiple fractures with spacing longer than or equal to the radiation beam diameter can be effectively identified.

Ultrasonic transducers are the basic core component of diagnostic imaging devices, wherein the piezoelectric materials are the active element of transducers. Recent studies showed that the alternating current poling (ACP) method could develop the properties of piezocomposites, which had great potential to improve transducer performance. Herein, transducers (fc = 3 MHz) made of DCP and ACP 1–3 piezocomposites (prepared by PZT-5H ceramics and PMN-PT single crystals) were fabricated. The effect of the ACP method on the bandwidth and insertion loss (sensitivity) was explored. The results indicate that the ACP method can significantly enhance the bandwidth and slightly increase the insertion loss of transducers. Particularly, a superhigh bandwidth of 142.8% was achieved in the transducer of ACP 1–3 PMN-PT single crystal combined with suitable matching and backing layers. This bandwidth is higher than that of all reported transducers with similar center frequency. Moreover, the optimization mechanism of transducer performance by the ACP method was discussed. The obtained results suggested that the ACP is an effective and convenient technology to improve transducer performances, especially for the bandwidth.

Glucose-dependent insulinotropic polypeptide (GIP) in combination with hyperinsulinemia increase blood flow and triglyceride clearance in subcutaneous abdominal adipose tissue in lean humans. The present experiments were performed to determine whether the increase involves capillary recruitment. Eight lean healthy volunteers were studied before and after 1 h infusion of GIP or saline during a hyperglycemic–hyperinsulinemic clamp, raising plasma glucose and insulin to postprandial levels. Subcutaneous abdominal adipose tissue blood flow (ATBF) was measured by the 133Xenon clearance technique, and microvascular blood volume was determined by contrast-enhanced ultrasound imaging.During infusion of saline and the clamp, both ATBF (2.7 ± 0.5 m L/min 100 g/tissue) and microvascular blood volume remained unchanged throughout the experiments. During GIP infusion and the clamp, ATBF increased ~fourfold to 11.4 ± 1.9 mL/min 100 g/tissue, P < 0.001. Likewise, the contrast-enhanced ultrasound signal intensity, a measure of the microvascular blood volume, increased significantly 1 h after in fusion of GIP and the clamp (P = 0.003), but not in the control experiments. In conclusion, the increase in ATBF during GIP infusion involves recruitment of capillaries in healthy lean subjects, which probably increases the interaction of circulating lipoproteins with lipoprotein lipase, thus promoting adipose tissue lipid uptake.

Subsurface radar imaging provides an insight into hidden scenes: For example, in security screening, radar can be used for the detection of dangerous objects or contraband. In non-destructive testing, radar imaging also allows to find internal material defects such as cracks or contaminations. Object contours and internal structures appear as echoes in the radar receive signal. The strongest echo typically is the one from the test object's surface. This echo can mask smaller echoes close to the surface and therefore, small inner structures may become invisible in the reconstruction image. To overcome this problem, we propose a novel concept to eliminate the surface echo in radar imaging. In contrast to existing surface elimination techniques, our approach can be used not only when screening objects with planar surfaces, but also on such that exhibit an unknown and possibly non-planar profile. Our approach is to combine radar and air-coupled ultrasound. Since air-coupled ultrasound cannot penetrate into solids, the receive signal only contains the echo from the test object's surface. The core of our concept is to generate radar and ultrasound signals with the same characteristics, i.e. they are equal in amplitude and phase. Then, the ultrasound data can be subtracted from the radar data and the resulting signal will only contain the echoes of the inner structures. When processing this data, the reconstructed images are almost free of reflections from the surface.

The fibrous porous structure of polymers can mimic the extracellular matrix of the native tissue, therefore such polymers have a good potential for use in regenerative medicine. Organs and tissues within the body exhibit different mechanical properties depending on their functionality, thus artificial scaffolds should have mechanical behaviors similar to the extracellular matrix in conditions like living organisms, primarily in aqueous media. Several methods have been investigated in aquatic environments, including noninvasive techniques based on ultrasonic focused beams for biological objectives. In this study we explored the tensile behavior of poly(L-lactide) nonwoven polymer scaffolds using high-frequency ultrasound microscopy combined with a horizontal testing machine, which provided a visualization of the reorganization and transformation of the dynamic volume microstructure. The mechanisms of unwinding, elongation, orientation, and deformation of polymer fibers under uniaxial tension were revealed. We observed an association between the lined plastic deformation from 100 to 400% and the formation of multiple necks in the fibers, which caused stress relaxation and significant rarefaction of the fibrous microstructure. It was shown that both peaks on the stress–strain curve corresponded to the microstructure of aligned fibers in terms of initial diameter and thinning fibers. We discuss the possible influence of these microstructure transformations on cell behavior.

In this study, an advanced semantic segmentation method and deep convolutional neural network was applied to identify the Breast Imaging Reporting and Data System (BI-RADS) lexicon for breast ultrasound images, thereby facilitating image interpretation and diagnosis by providing radiologists an objective second opinion. A total of 684 images (380 benign and 308 malignant tumours) from 343 patients (190 benign and 153 malignant breast tumour patients) were analysed in this study. Six malignancy-related standardised BI-RADS features were selected after analysis. The DeepLab v3+ architecture and four decode networks were used, and their semantic segmentation performance was evaluated and compared. Subsequently, DeepLab v3+ with the ResNet-50 decoder showed the best performance in semantic segmentation, with a mean accuracy and mean intersection over union (IU) of 44.04% and 34.92%, respectively. The weighted IU was 84.36%. For the diagnostic performance, the area under the curve was 83.32%. This study aimed to automate identification of the malignant BI-RADS lexicon on breast ultrasound images to facilitate diagnosis and improve its quality. The evaluation showed that DeepLab v3+ with the ResNet-50 decoder was suitable for solving this problem, offering a better balance of performance and computational resource usage than a fully connected network and other decoders.

Porosity ranging from 0.15% to 2.33% in carbon fiber-reinforced polymer composites (CFRPs) is detected and characterized by multi-mode visualizations including ultrasonic A-Scan, B-Scan, C-Scan and Tomography-Scan using a focused ultrasonic transducer. Three-dimensional visualizations are also reconstituted from the ultrasonic tomography scan images. The result shows: UT using the focused transducer possesses high sensitivity, near-surface resolution and depth estimation for porosity in composites. Using this transducer, multi-mode visualizations can characterize porosity feature and fiber orientations through the entire volume. The amplitude and transit time of A-Scan waveforms have correlations with porosity size and depth. B-Scan imaging characterizes porosity distribution with depth estimation up to one-ply thickness, which is approximate 0.18 mm. C-Scan imaging characterizes porosity size and distribution in the integral composite bulk. Tomography scan can give detailed information about porosity feature and fiber orientations ply by ply, with detection sensitivity of no more than 1.0 mm and excellent near-surface resolution of one ply.

As traditional ultrasonic imaging systems (UIS) are expensive, bulky, and power-consuming, miniaturized and portable UIS have been developed and widely utilized in the biomedical field. The performance of integrated circuits (ICs) in portable UIS obviously affects the effectiveness and quality of ultrasonic imaging. In the ICs for UIS, the analog-to-digital converter (ADC) is used to complete the conversion of the analog echo signal received by the analog front end into digital for further processing by a digital signal processing (DSP) or microcontroller unit (MCU). The accuracy and speed of the ADC determine the precision and efficiency of UIS. Therefore, it is necessary to systematically review and summarize the characteristics of different types of ADCs for UIS, which can provide valuable guidance to design and fabricate high-performance ADC for miniaturized high resolution UIS. In this paper, the architecture and performance of ADC for UIS, including successive approximation register (SAR) ADC, sigma-delta (Σ-∆) ADC, pipelined ADC, and hybrid ADC, have been systematically introduced. In addition, comparisons and discussions of different types of ADCs are presented. Finally, this paper is summarized, and presents the challenges and prospects of ADC ICs for miniaturized high resolution UIS.

Magnetomotive Ultrasound is an imaging technique that is capable to detect tissue, which is perfused by magnetic nanoparticles. However, this modality is restricted to qualitative imaging only. Therefore, we present an extended Magnetomotive Ultrasound algorithm, which allows the quantitative determination of the spatial distribution of magnetic nanoparticle density in tissue. The algorithm is based on an iterative adjustment of simulated data to measurements. Experiments with tissue-mimicking phantoms reveal that the presented method leads to the spatial particle concentration in the correct order of magnitude.

The aim of this study was to identify sequential changes in the actual sites and shapes of wrist structures on the high-resolution sectioned images and to compare these with those on ultrasound (US) images. These images of the wrist may yield guidelines for diagnosing various pathological lesions in the wrist. In the sectioned images of a whole cadaver body, and the images including the wrist were selected, and part of the hand was cropped. A wrist of one healthy Korean subject was scanned by ultrasonography to obtain US images of the wrist. Wrist structures were identified and labeled in detail on the sectioned images and the corresponding US images. Serial changes of the sites and shapes of the wrist structures mainly occurred in the bones, median nerve, ulnar artery, ulnar nerve, and the flexor pollicis longus tendon, along with thickening of the thenar and hypothenar muscles. The present results could provide a new guide for anatomy mapping, diagnosing, and detecting various lesions of the wrist. They can also be useful and effective for educational purposes related to interpreting US images.

In this study, we applied semantic segmentation using a fully convolutional deep learning network to identify characteristics of the Breast Imaging Reporting and Data System (BI-RADS) lexicon from breast ultrasound images to facilitate clinical malignancy tumor classification. Among 378 images (204 benign and 174 malignant images) from 189 patients (102 benign breast tumor patients and 87 malignant patients), we identified seven malignant characteristics related to the BI-RADS lexicon in breast ultrasound. The mean accuracy and mean IU of the semantic segmentation were 32.82% and 28.88, respectively. The weighted intersection over union was 85.35%, and the area under the curve was 89.47%, showing better performance than similar semantic segmentation networks, SegNet and U-Net, in the same dataset. Our results suggest that the utilization of a deep learning network in combination with the BI-RADS lexicon can be an important supplemental tool when using ultrasound to diagnose breast malignancy.

The analysis of the beampattern is the base of sparse arrays design process. However, in the case of bidimensional arrays, this analysis has a high computational cost, turning the design process into a long and complex task. If the imaging system development is considered a holistic process, the aperture is a sampling grid that must be considered in the spatial domain through the coarray structure. Here, we propose to guide the aperture design process using statistical parameters of the distribution of the weights in the coarray. We have studied three designs of sparse matrix binned arrays with different sparseness degrees. Our results prove that there is a relationship between these parameters and the beampattern, which is valuable and improves the array design process. The proposed methodology reduces the computational cost up to 58 times with respect to the conventional fitness function based on the beampattern analysis.

This work provides a guide to design ultrasonic synthetic aperture systems for non-grid two-dimensional sparse arrays such as spirals or annular segmented arrays. It presents an algorithm that identifies which elements have a more significant impact on the beampattern characteristics and uses this information to reduce the number of signals, the number of emitters and the number of parallel receiver channels involved in the beamforming process. Consequently, we can optimise the 3D synthetic aperture ultrasonic imaging system for a specific sparse array, reducing the computational cost, the hardware requirements and the system complexity. Simulations using a Fermat spiral array and experimental data based on an annular segmented array with 64 elements are used to assess this algorithm.

Nowadays the development of automated inspection systems based on six degrees of freedom robotic manipulators is a highly relevant topic in ultrasonic non-destructive testing. One of the issues associated with such development is the problem of acquiring high-resolution results. In this article, the application Phase-Reversal Fresnel Zone Plates is considered for solving this problem. Such acoustic lenses can solve the task of high-resolution results acquisition by using a single unfocused transducer. Furthermore, Phase-Reversal Fresnel Zone Plates can provide the desired focusing depth with the fixed thickness of the coupling layer. It is important in the case of application of devices which provide localized coupling. In this paper a proper design of Phase-Reversal Fresnel Zone Plate was determined according to the conditions of planned experiments. Its efficiency was verified via the Finite Element Method modeling. In all performed experiments the relative error of flaws size estimation did not exceed 6% whereas the signal-to-noise ratio was not lower than 17.1 dB. Thus, experimental results demonstrate that the application of Phase-Reversal Fresnel Zone Plates allowed to obtain results with high lateral resolution and signal-to-noise ratio. These results demonstrate the reasonability of the development of devices that provide localized coupling and use Phase-Reversal Fresnel Zone Plates.

The nondestructive inspection of concrete structures is indispensable for ensuring the safety and reliability of aging infrastructures. Ultrasonic waves having a frequency of tens of kHz are frequently used to reduce the scattering attenuation due to coarse aggregates. Such low frequencies enable the measurement of the thickness of concrete structures and detection of layer-type defects, such as delamination, whereas it causes a lack of sensitivity to crack-type defects. In this paper, to realize the ultrasonic phased array (PA) imaging of crack-type defects, we fabricated a low-frequency (LF) array transducer with a center frequency of hundreds of kHz. To avoid the crosstalk between piezoelectric elements and dampen the vibration of each element, we adopted soft lead zirconate titanate (soft PZT) with a low mechanical quality factor. Subsequently, we optimized the geometry of each piezoelectric element using a finite element method to generate a short pulse. After validating the design in a fundamental experiment using a single-element transducer, we fabricated a 32-element array transducer with a center frequency of 350 kHz. To show the imaging capability of the LF array transducer, we applied it to a concrete specimen with a delamination. As a result, the PA with the LF array transducer clearly visualized the delamination, which could not be visualized using the PA with a 2.5 MHz array transducer. Furthermore, we applied it to a more challenging defect, a slit, which is sometimes used to simulate crack-type defects. As a result, the PA with the LF array transducer clearly visualized a slit of 1 mm width and 40 mm height in a concrete specimen. Thus, we demonstrated the usefulness of the LF array transducer for inspecting crack-type defects.

An easily multiplexed fiber-optic Fabry-Perot interferometer (FPI)-based ultrasonic wave (UW) sensor has been proposed and used to experimentally demonstrate ultrasound wave imaging of seismic-physical models. The sensor probe comprises an interferometer formed by a free-standing gold foil and a cleaved optic-fiber tip. An acoustic focusing lens enhances the sensor's ultrasound sensitivity and assists with capability to multiplex multiple probes. Theoretical modeling of the focusing effect of the acoustic lenses and the ultrasonic responses of the probes are presented and analyzed. We present an experimental demonstration of time-division multiplexing of three fiber-optic Fabry-Perot sensors operating in air to reconstruct the shapes of physical models. The compact sensor has a symmetrical structure so that it presents a good directionality of ultrasound detection, making it valuable as an effective sensor for ultrasound scanning of physical models in air.

Research in biomedical nanotechnology led already to a variety of applications of nanoparticles in diagnosis as well as in therapy. One of these medical applications is Magnetic Drug Targeting, a promising cancer treatment technique. The aim of this medical attendance is a local chemotherapeutic treatment of the cancerous tissue. For this purpose, chemotherapeutic drugs are bound to magnetic nanoparticles and accumulated in the tumor area by means of an external static magnetic field. Hereby, a well-defined particle concentration in the cancerous tissue requires monitoring of the particle accumulation. Therefore, we present an ultrasound imaging technique that is capable of detecting quantitatively the concentration of iron oxide nanoparticles in biological tissue. The evaluation is based on the variation of the speed of sound of an induced shear wave with respect to the particle concentration.

High-intensity focused ultrasound (HIFU) therapy represents an image-guided and non-invasive surgical approach to treat uterine fibroid. During the HIFU operation, it is challenging to obtain the real-time and accurate lesion contour automatically in ultrasound (US) video. The current intraoperative image processing is completed manually or semi-automatic. In this Letter, the authors propose a morphological active contour without an edge-based model to obtain accurate real-time and non-rigid US lesion contour. Firstly, a targeted image pre-processing procedure is applied to reduce the influence of inadequate image quality. Then, an improved morphological contour detection method with a customised morphological kernel is harnessed to solve the low signal-to-noise ratio of HIFU US images and obtain an accurate non-rigid lesion contour. A more reasonable lesion tracking procedure is proposed to improve tracking accuracy especially in the case of large displacement and incomplete lesion area. The entire framework is accelerated by the GPU to achieve a high frame rate. Finally, a non-rigid, real-time and accurate lesion contouring for intraoperative US video is provided to the doctor. The proposed procedure could reach a speed of more than 30 frames per second in general computer and a Dice similarity coefficient of 90.67% and Intersection over Union of 90.14%.

Time of flight diffraction (TOFD) is considered a reliable non-destructive testing method for the inspection of welds using a pair of single-element probes. On the other hand, ultrasonic phased array imaging has been continuously developed over the last couple of decades, and now features powerful algorithms, such as the total focusing method (TFM) and its multi-view approach to rendering detailed images of inspected parts. This article focuses on a different implementation of the TFM algorithm, relying on the coherent summation of the instantaneous signal phase. This approach presents a wide range of benefits, such as removing the need for calibration, and is highly sensitive to defect tips. This study compares the sizing and localization capabilities of the proposed method with the well-known TOFD. Both instantaneous phase algorithm and TOFD do not take advantage of the signal amplitude. Experimental tests were performed on a ¾″-thick steel sample with crack-like defects at different angles. Phase-based imaging techniques showed similar characterization capabilities as the standard TOFD method. However, the proposed method adds the benefit of generating an easy-to-interpret image that can help in localizing the defect. These results pave the way for a new characterization approach, especially in the field of automated ultrasonic testing (AUT).

Plane wave imaging (PWI) is attracting more attention in industrial nondestructive testing and evaluation (NDT&E). To further improve imaging quality and reduce reconstruction time in ultrasonic imaging with a limited active aperture, an optimized PWI algorithm was proposed for rapid ultrasonic inspection, with the comparison of the total focusing method (TFM). The effective area of plane waves and the space weighting factor were defined in order to balance the amplitude of the imaging area. Experiments were carried out to contrast the image quality, with great agreement to the simulation results. Compared with TFM imaging, the space-optimized PWI algorithm demonstrated a wider dynamic detection range and a higher defects amplitude, where the maximum defect amplitude attenuation declined by 6.7 dB and average attenuation on 12 defects decreased by 3.1 dB. In addition, the effects of plane wave numbers on attenuation and reconstruction time were focused on, achieving more than 10 times reduction of reconstruction times over TFM.