Ultrasonic Imaging Research Articles

A transceiver integrated piezoelectric micromachined ultrasound transducer array for underwater imaging

In this article, a scandium-doped aluminum nitride (Sc0.2Al0.8N) piezoelectric micromachined ultrasound transducer (PMUT) array for underwater imaging is presented. The reported PMUT array integrates a transmitter and a receiver in one transduction cell, in which the outer top electrode is used for transmitting while the inner top electrode is employed for simultaneously receiving ultrasonic waves, respectively. A 7 × 8 transduction cell array with characteristic size of 500μm is designed in a bioinspired honeycomb architecture and developed based on a piezoelectric on silicon-on-insulator (SOI) platform. The top electrode of the transduction cell is split into the outer and inner sections with the optimized size ratio for achieving transceiver integration in one cell. The fabricated PMUT array exhibits a transmit sensitivity of 146.59 dB (re: 1 μPa/V), and a receive sensitivity of −173.70 dB (re: 1 V/μPa) at its resonant frequency of around 150 kHz in water. In order to demonstrate the feasibility of underwater imaging, the PMUT array and its signal conditional circuits are packaged using an acoustically transparent material. Ultrasonic pulse-echo imaging with the developed PMUT array is demonstrated without implementation of a switching circuit to separate the transmit and reflected signals, due to the transceiver integration approach proposed in our work. This work demonstrates the feasibility of underwater imaging for the transceiver integrated PMUT array, which has great commercial value for minimized and portable underwater imaging.

Time- Versus Frequency-Domain Inverse Elastic Scattering: Theory and Experiment

This study formally adapts the time-domain linear sampling method (TLSM) for ultrasonic imaging of stationary and evolving fractures in safety-critical components. The TLSM indicator is then applied to the laboratory test data of [F. Pourahmadian and H. Yue, Inverse Problems, 37 (2021), 055012; F. Pourahmadian, Mech. Syst. Signal Process., 161 (2021), 108029] and the obtained reconstructions are compared to their frequency-domain counterparts. The results highlight the unique capability of the time-domain imaging functional for high-fidelity tracking of evolving damage, and its relative robustness to sparse and reduced-aperture data at moderate noise levels. A comparative analysis of the TLSM images against the multifrequency LSM maps of [F. Pourahmadian and H. Yue, Inverse Problems, 37 (2021), 055012] further reveals that thanks to the full-waveform inversion in time and space, the TLSM generates images of remarkably higher quality with the same dataset.

Kinetic energy as a factor in assessing the work of the heart in patients with aortic stenosis

Goal. To analyze the evolution of the myocardial contraction force through the assessment of kinetic energy in patients with aortic stenosis based on intraventricular blood flowsMaterial and methods. According to the selection criteria, 21 healthy volunteers (age 34 ± 3) and 105 patients with aortic stenosis (age 62 ± 4) were examined before and after surgery for 7–10 days. Transthoracic echocardiography was performed on a Vivid E9 device in 2, 3 and 4 chamber positions with registration of intraventricular blood flows, calculation of the rate of change in volume and kinetic energy depending on the left ventricular EDV, pressure gradient (ΔP) on the aortic valve with an assessment of the displacement of the left ventricular endocardium contour, based on technologies for tracking speckles of ultrasonic images in the MultiVox program.Results. Our goal was to quantify kinetic energy (KE) during the entire cardiac cycle of the left ventricle (LV) using echocardiography. One of the main strengths identified in these studies is the high reproducibility of the assessment of LV blood flow and hemodynamics the average coefficient of variability 7 ± 2% for assessing LV function. Studies have shown increased diagnostic reliability without spending additional time. In systole, the KE before the LV operation was higher than normal values (0.62–0.78 J) after the operation, the KE approached the norm, averaging 0.55 J.Conclusion. Changes in intraventricular blood flow in patients with pressure overload of the heart demonstrate higher systolic energy compared to the control group. Different time values of energy in systole and diastole, observed in patients before surgery, represent an objective approach to assessing the work of the heart. The energy analysis reflects earlier signs of mechanical myocardial disorders, compared with the ejection fraction and, possibly, predict the development of cardiac remodeling. Adequate correction of the defect normalizes the work of the heart already in the early postoperative period.

An improved Fourier Ptychography algorithm for ultrasonic array imaging

Inspired by the optical imaging algorithm, the Fourier Ptychography (FP) algorithm is adopted to improve the resolution of ultrasonic array imaging. In the FP algorithm, the steady-state spectrum is utilized to recover the high-resolution ultrasonic images. Meanwhile, the parameters of FP algorithm are empirical, which can affect the imaging quality of ultrasonic array. Then the particle swarm optimization (PSO) algorithm is used to optimize the parameters of FP algorithm to further improve the imaging quality of ultrasonic array. The tungsten imaging experiments and pig eye imaging experiments are conducted to demonstrate the feasibility and effectiveness of the developed algorithm. In addition, the proposed algorithm and the coherent wave superposition (CWS) algorithm are both based on single plane wave (SPW) algorithms and they are then compared. The results show that the CWS algorithm and FP algorithm have good longitudinal and lateral resolutions, respectively. The particle swarm optimization-based FP (PSOFP) imaging algorithm has both excellent lateral and longitudinal resolutions. The average lateral resolution of PSOFP imaging algorithm is improved by 34.47% compared with CWS imaging algorithm in the tungsten wires experiments, and the lateral boundary structure width of the lens is improved by 49.48% in the pig eye experiments. The proposed algorithm can effectively improve the ultrasonic imaging quality for medical application.

Photoacoustic imaging on its way toward clinical utility: a tutorial review focusing on practical application in medicine.

Photoacoustic imaging (PAI) enables the visualization of optical contrast with ultrasonic imaging. It is a field of intense research, with great promise for clinical application. Understanding the principles of PAI is important for engineering research and image interpretation. In this tutorial review, we lay out the imaging physics, instrumentation requirements, standardization, and some practical examples for (junior) researchers, who have an interest in developing PAI systems and applications for clinical translation or applying PAI in clinical research. We discuss PAI principles and implementation in a shared context, emphasizing technical solutions that are amenable to broad clinical deployment, considering factors such as robustness, mobility, and cost in addition to image quality and quantification. Photoacoustics, capitalizing on endogenous contrast or administered contrast agents that are approved for human use, yields highly informative images in clinical settings, which can support diagnosis and interventions in the future. PAI offers unique image contrast that has been demonstrated in a broad set of clinical scenarios. The transition of PAI from a "nice-to-have" to a "need-to-have" modality will require dedicated clinical studies that evaluate therapeutic decision-making based on PAI and consideration of the actual value for patients and clinicians, compared with the associated cost.

Optimized ultrasonic total focusing imaging of diverse and multiple defects in crossply CFRP: Floquet wave theory, numerical simulation, and experimental validation

Carbon fiber reinforced polymers (CFRPs) with large thickness (≥20 mm) are being extensively used for aerospace structures, and are prone to the manufacturing and in-service defects due to the complexity and difficulty of manufacturing. This study addresses an intensive interrogation of multi-parameter optimization towards a high-quality ultrasonic total focusing method (TFM) imaging for diverse and multiple defects in crossply CFRP. Firstly, material parameters of unidirectional laminate are inversely constructed based on Christoffel equation by inputting the experimentally measured wave speed, based on which the wave speed and homogenization region for the crossply CFRP are obtained with the Floquet wave theory. Then, the wave propagation at crossply CFRP with preset side drilled holes (SDHs) at depths of 4 mm and 12 mm is modelled, from which the full matrix data are extracted for TFM imaging using multiple parameter optimization, including wave velocity correction, propagation restriction angle, and wave central frequency. With the proposed signal-to-noise ratio as the criterion of TFM imaging quality, the combined parameters for optimized imaging are sorted out, which are strongly related to the feature of propagating and non-propagating waves calculated with the Floquet wave homogenization theory. A further experimental validation is performed to image multiple SDHs and delamination with size over 2 mm and depths covering 2.5 mm to 17.5 mm. This systematic analysis of parameter optimization for TFM imaging in thick CFRP sets up the foundation for the TFM towards a real engineering application of CFRP detection.

Anisotropy Evaluation and Defect Detection on Laser Power Bed Fusion 316L Stainless Steel.

Because of rapid heating, cooling, and solidification during metal additive manufacturing (AM), the resulting products exhibit strong anisotropy and are at risk of quality problems from metallurgical defects. The defects and anisotropy affect the fatigue resistance and material properties, including mechanical, electrical, and magnetic properties, which limit the applications of the additively manufactured components in the field of engineering. In this study, the anisotropy of laser power bed fusion 316L stainless steel components was first measured by conventional destructive approaches using metallographic methods, X-ray diffraction (XRD), and electron backscatter diffraction (EBSD). Then, anisotropy was also evaluated by ultrasonic nondestructive characterization using the wave speed, attenuation, and diffuse backscatter results. The results from the destructive and nondestructive methods were compared. The wave speed fluctuated in a small range, while the attenuation and diffuse backscatter results were varied depending on the build direction. Furthermore, a laser power bed fusion 316L stainless steel sample with a series of artificial defects along the build direction was investigated via laser ultrasonic testing, which is more commonly used for AM defect detection. The corresponding ultrasonic imaging was improved with the synthetic aperture focusing technique (SAFT), which was found to be in good agreement with the results from the digital radiograph (DR). The outcomes of this study provide additional information for anisotropy evaluation and defect detection for improving the quality of additively manufactured products.

Ultrasonic adaptive plane wave high-resolution imaging based on convolutional neural network

Components with complex surfaces can pose a challenge for achieving phased array ultrasonic testing. Although coupling issues can be addressed by immersing or adding plexiglass wedges, obtaining high-quality images in a short time remains difficult under such conditions. This paper proposes an adaptive plane wave imaging scheme to address these challenges. First, the interface is reconstructed using a plane wave priority echo estimation method. Then, a beamforming algorithm adapted to the irregular interface is used to generate low-resolution (LR) images, which are then reconstructed into high-resolution (HR) images in a short time with convolutional neural network (CNN). The CNN is trained with simulation data, and the defects of test blocks and wheel rim are tested. Experimental results show that the reconstruction method combined with CNN significantly improves imaging quality and speed compared to the conventional adaptive plane wave beamforming algorithm based on the time-domain physical model.

Measurements of the Thickness and Area of Thick Oil Slicks Using Ultrasonic and Image Processing Methods

The in situ measurement of thick oil slick thickness (>0.5 mm) and area in real time in order to estimate the volume of an oil spill is very important for determining the oil spill response strategy and evaluating the oil spill disposal efficiency. In this article, a method is proposed to assess the volume of oil slicks by simultaneously measuring the thick oil slick thickness and area using ultrasonic inspection and image processing methods, respectively. A remotely operated vehicle (ROV), integrating two ultrasonic immersion transducers, was implemented as a platform to receive ultrasonic reflections from an oil slick. The oil slick thickness was determined by multiplying the speed of sound by the ultrasonic traveling time within the oil slick, which was calculated using the cross-correlation method. Images of the oil slick were captured by an optical camera using an airborne drone. The oil slick area was calculated by conducting image processing on images of the oil slick using the proposed image processing algorithms. Multiple measurements were performed to verify the proposed method in the laboratory experiments. The results show that the thickness, area and volume of a thick oil slick can be accurately measured with the proposed method. The method could potentially be used as an applicable tool for measuring the volume of an oil slick during an oil spill response.

FCG-Net: An innovative full-scale connected network for thyroid nodule segmentation in ultrasound images

Ultrasonic imaging is more susceptible to poor contrast and speckle noise than other imaging modalities, which poses certain challenges to computer-aided automatic segmentation of thyroid nodules. Nine popular segmentation networks for thyroid nodule in ultrasound images were well trained with the same training strategy and the performances on the public dataset and the clinical dataset were well compared using different indicators. Among them, UNet3+ achieved the best performance. However, it brings more parameters compared to other lightweight networks, which limits its application in portable diagnosis. This paper proposed an innovative thyroid nodule segmentation network FCG-Net that using full-scale skip connection to extracted multi resolution features, and Ghost bottleneck was introduced in the encoder and decoder process to reduce computational complexity of feature maps. Compared to UNet3+, the parameters of the model were reduced from 27 million to 11 million, and the inference speed was improved by 1.07 FPS. Meanwhile, the segmentation performance of FCG-Net exceeds that of UNet3+. 729 ultrasound images from the public dataset and clinical ultrasound images were used to validate the performance of the network by 5-fold cross-validation. The accuracy, precision, sensitivity, specificity and Dice of the FCG-Net were 0.9488, 0.8579, 0.8984, 0.9627 and 0.8670 respectively. The network not only improves the accuracy of ultrasonic diagnosis but also reduces the requirements of hardware and calculation, which is significant to promote the development of portable ultrasonic diagnosis of thyroid nodule.

Thoughts and Concepts in Ultrasonography-guided Hyaluronidase Injection Technique.

INTRODUCTION The number of people receiving facial filler injections for aesthetic purpose has been increasing in recent years. Simultaneously, the number of patients dissolving fillers due to unsatisfactory outcomes or adverse effects, such as granuloma and allergy, is also increasing. Hyaluronidase has various uses, including dissolving hyaluronic acid fillers and treating granulomatous foreign body reactions and necrosis associated with filler injections.1 Here, I will discuss why ultrasonography should be performed before a filler dissolving injection and why the filler should be dissolved while viewing ultrasonographic images.2 Hyaluronidase is an endoglycosidase that breaks down hyaluronic acid into monosaccharides by cleaving its glycosidic bonds.3,4 Safe performance of this method requires sufficient understanding of the anatomy of the face, because of the heavy distribution of vital blood vessels, nerves, retaining ligaments, and muscles.5 The author performed filler removal using ultrasonography on more than 500 patients. First, palpation was performed, and after confirming the exact location and depth with ultrasound, it was marked with a pen. The filler was removed by injection of hyaluronidase. Some people had swelling and heat due to allergy to hyaluronidase, but they improved within 2–3 days and did not experience any other side effects (Fig. 1). This ultrasonography-guided hyaluronidase injection technique offers several advantages, as follows:Fig 1.: Pre- and post-procedure ultrasonic images. A, Filler in the anterior cheek shown before hyaluronidase injection. B, Anterior cheek after the filler has been completely dissolved. Ultrasonography is rapid and simple, with no risk of radiation exposure. This technique involves no additional discomfort for patients and can be more comfortable. This method does not require injection into a wide area around the injected filler, indicating that a smaller amount of hyaluronidase can be used. Vital blood vessels and nerves can be avoided using ultrasonographic images. When catastrophic adverse effects (such as blindness or necrosis) occur, exacerbation of such adverse effects can be quickly and accurately prevented. This method can effectively dissolve the filler, as the target is accurately set beforehand. In cases wherein undissolved fillers are still present despite several dissolution procedures, ultrasonography-guided hyaluronidase injection before removing the filler by incision is a feasible approach for both the patient and the physician. A limitation is that it is very difficult to completely remove granuloma or filler if it remains in a very small size, or if the filler is broken into very small sizes by melting it. In addition, there are cases in which the filler cannot be confirmed by ultrasound. The use of more precise ultrasound is necessary. This study is a conceptual thought and represents the author’s opinion based on experience, and a more scientific study with 500 patients will be conducted in the future. DISCLOSURE The author has no financial interest to declare in relation to the content of this article.

Ultrasonic tomography imaging enhancement approach based on deep convolutional neural networks.

The containment liner plate (CLP) is a thin layer of carbon steel material applied as a base for concrete structures protecting nuclear material. The structural health monitoring of the CLP is critical to ensure the safety of nuclear power plants. Hidden defects in the CLP can be identified utilizing ultrasonic tomographic imaging techniques such as the reconstruction algorithm for the probabilistic inspection of damage (RAPID) methodology. However, Lamb waves have a multimodal dispersion feature, which makes the selection of a single mode more difficult. Thus, sensitivity analysis was utilized since it allows for the determination of each mode's level of sensitivity as a function of frequency; the S0 mode was chosen after examining the sensitivity. Even though proper Lamb wave mode was selected, the tomographic image had blurred zones. Blurring reduces the precision of an ultrasonic image and makes it more difficult to distinguish the dimensions of the flaw. To enhance the tomographic image of the CLP, deep learning architecture such as U-Net was utilized for the segmentation of the experimental ultrasonic tomographic image, which includes an encoder and decoder part for better visualization of the tomographic image. Nevertheless, collecting enough ultrasonic images to train the U-Net model was not economically feasible, and only a small number of the CLP specimens can be tested. Thus, it was necessary to utilize transfer learning and get the values of the parameters from a pre-trained model with a much larger dataset as a starting point for a new task, rather than training a new model from scratch. Through these deep learning approaches, we were able to eliminate the blurred section of the ultrasonic tomography, leading to images with clear edges of defects and no blurred zones.

Application of PDSA Circulation in Carotid Artery Ultrasound Screening for High-Risk Individuals with Stroke

<i>Objective</i> To explore the application effect of PDSA circulation in improving the quality of carotid artery ultrasound screening in high-risk populations for stroke. <i>Methods</i> Refer to PDSA cycle, Randomly select 600 image and text reports (including images and text descriptions) of carotid artery ultrasonic examination from January 2021 to December 2021 in the ultrasonic medical image information system, scored according to the quality scoring standard; The goal of this time is to achieve more than 95% of the reports of Class A image and texts, propose solutions to the problems of image quality and text description in the report. Formulate countermeasures from May to June 2021. Take 50 carotid ultrasound image and text reports after implementing various improvement measures from November 2021 to December 2021 for scoring, compare the differences between 2022 and 2021 ultrasonic image text reports and clinical satisfaction scores. Analyze the changes of image text reports and clinical satisfaction scores before and after the implementation of PDSA cycle, and continuously optimize the carotid ultrasound examination process through training and learning, discussion within the department, and collection of clinical feedback. <i>Result</i> Before implementing the PDSA process of standardized medical quality management, the score of carotid ultrasound image and text reports was (87.46±5.82), the clinical satisfaction was (84.46±6.42), and the number of A-class image and text reports accounted for 58% (348/600); After the implementation of the standardized medical quality management PDSA process, the score of graphic reports increased to (92.74±3.55) points, and the clinical satisfaction increased to (93.14±3.86) points. The number of Class A graphic reports accounted for 82% (492/600), with statistically significant differences (all <I>P</I><0.05). <i>Conclusion</i> PDSA circulation has effectively improved the image and text report of carotid ultrasound screening and clinical satisfaction score, which can be applied to the quality control of other single diseases in the ultrasound department, so as to improve the medical quality of the ultrasound department.

Low-Frequency ultrasonic tomography of Corrosion-induced damage patterns on naturally corroded solid reinforcing bar rock bolts

A combined non-destructive guided ultrasonic wave measuring approach and low-frequency ultrasonic tomography technique on cylindrical surfaces is developed to investigate corrosion-induced damage patterns in naturally corroded 60-year-old solid rebars. The main goal of low-frequency tomographic imaging simulations is for differential detection of general and localized pitting corrosions on cylindrical surfaces of solid steel bars. The modified damage probabilistic reconstruction algorithm for cylindrical surfaces is also adopted to simulate naturally general and localized pitting corrosion patterns. To increase the ray density or resolution of images, a regular array of accelerometer sensors with high-density spatial distributions around the cylindrical surface of steel bars is installed for a fixed piezocomposite actuator. As such, an efficient sensor deployment method can be applied with the trilateration technique to achieve effective coverage and connectivity properties between accelerometer sensors. Stochastic signal processing which is elicited from the Hilbert-Huang Transform (HHT) signal method is also employed to analysis low-frequency tomography time domain algorithms. Finally, optical surface profilometry approaches, and static state tensile testings, together with scanning electron microscopy (SEM) are adopted to confirm the effectiveness of non-destructive and tomography imaging techniques. The results show that the guided wave signals with excitation frequency of less than 10 kHz can be precisely employed to identify the general and localized pitting corrosion distributions on the cylindrical surfaces of steel bars and qualitatively reconstruct them using low-frequency ultrasonic tomography simulations. This research study also demonstrates that the low-frequency ultrasonic tomography simulations can be effectively applied in corrosion pattern uncertainty modelling.

Method to detect the bolt thread defect in the aerospace vehicle with ultrasonic image and its implementation

PurposeThis study aims to solve the problems of ambiguous localization, large calculation, poor real-time and limited applicability of bolt thread defect detection.Design/methodology/approachFirst, the acquired ultrasound image is used to acquire the larger area of the image, which is set as the compliant threaded area. Second, based on the determined coordinates of the center point in each selected region, the set of coordinates on the left and right sides of the bolts is acquired by DBSCAN method with parameters eps and MinPts, which is determined by data set dimension D and the k-distance curve. Finally, the defect detection boundary line fitting is completed using the acquired coordinate set, and the relationship between the distance from each detection point to the curve and d, which is obtained from the measurement of the standard bolt sample with known thread defect, is used to locate the bolt thread defect simultaneously.FindingsIn this paper, the bolt thread defect detection method with ultrasonic image is proposed; meanwhile, the ultrasonic image acquisition system is designed to complete the real-time localization of bolt thread defects.Originality/valueThe detection results show that the method can effectively detect bolt thread defects and locate the bolt thread defect location with wide applicability, small calculation and good real-time performance.

The petrophysical characteristics of Macabu formation (Aptian, Campos Basin) continental carbonates: Core and special well logs (UBI and NMR) analysis integration

To interpret carbonate heterogeneities and understand the correlation between these rock features and their petrophysical parameters, an integrated dataset formed by thin section, core sample description, image log, and nuclear magnetic resonance analysis were used. This interactive approach enables the comparison of depositional and acoustic image log facies and their permo-porous behaviors. The advantage of the proposed integration lies in the ability to expand the interpretation of depositional facies to the entire imaged well interval. The results highlight the occurrence of six depositional facies, four ultrasonic image log facies, and two intervals with different permo-porous behavior present at Macabu Formation (Aptian, Campos Basin). Based on core sample and thin section analysis, three in situ carbonates were described: F1 – shrubstones, F2 - spherulitic grainstone-wackstone and hybrid forms, F3 - stevensitic claystone with spherulites, and others like transported facies: F4 - intraclastic grainstone-rudstone, F5 - laminated Detrital packstone-grainstone, and F6 - laminated dolomudstone. According to ultrasonic signal amplitude and structural patterns, such as descriptive criteria, the ultrasonic image log facies characterization resulted in: UIF1 - bright-heterogeneous, UIF2 - dark laminated, UIF3 - bright massive, and UIF4 - dark dendritic. The NMR well log analysis helped us divide the formation into two main zones, the first with good reservoir behavior and the other with poor behavior. This approach resulted in the correlation between facies and reservoir quality, indicating those with better fluid flow potential, in which facies F1, F2, F4, and UIF4 showed the best results. Finally, the integration between the different facies analysis demonstrated that several lithofacies may have the same appearance in the acoustic image, leading them to integrate the same ultrasonic image facie, this occurs due to their similarity in roughness.

Active contour and texture features hybrid model for breast cancer detection from ultrasonic images

AbstractBreast ultrasound is commonly used in the early detection of breast cancer. The existing geodesic‐based methods use pre‐defined filters that necessitate extensive prior knowledge to achieve the region of interest in input image. Furthermore, the majority of ultrasound images suffer from noise and acoustic shadowing, which reduces the accuracy of tumor detection. To make the breast ultrasound image more informative, the discriminative features can also be extracted to improve detection accuracy. This article proposes a method to combine Active Contour and Texture Feature Vectors to find discriminative patterns. A comprehensive set of discriminative features for cancer detection in ultrasound images is created by combining the two learning models. The Breast Ultrasound Images dataset is used to evaluate the suggested method and compare it to recently created algorithms. Experimental results reveal that the proposed approach outperforms the existing algorithms in terms of accuracy, recall, precision, Jaccard index, and F1 score.

Association between ultrasound BI-RADS signs and molecular typing of invasive breast cancer.

To explore the correlation between ultrasound images and molecular typing of invasive breast cancer, so as to analyze the predictive value of preoperative ultrasound for invasive breast cancer. 302 invasive breast cancer patients were enrolled in Heping Hospital affiliated to Changzhi Medical College in Shanxi, China during 2020 to 2022. All patients accepted ultrasonic and pathological examination, and all pathological tissues received molecular typing with immunohistochemical (IHC) staining. The relevance between different molecular typings and ultrasonic image, pathology were evaluated. Univariate analysis: among the four molecular typings, there were significant differences in tumor size, shape, margin, lymph node and histological grade (P<0.05). 1. Size: Luminal A tumor was smaller (69.4%), Basal -like type tumors are mostly larger (60.9%); 2. Shape: Basal-like type is more likely to show regular shape (45.7%); 3. Margin: Luminal A and Luminal B mostly are not circumscribed (79.6%, 74.8%), Basal -like type shows circumscribed(52.2%); 4. Lymph nodes: Luminal A type tends to be normal (87.8%), Luminal B type,Her-2+ type and Basal-like type tend to be abnormal (35.6%,36.4% and 39.1%). There was no significant difference in mass orientation, echo pattern, rear echo and calcification (P>0.05). Multivariate analysis: Basal-like breast cancer mostly showed regular shape, circumscribed margin and abnormal lymph nodes (P<0.05). There are differences in the ultrasound manifestations of different molecular typings of breast cancer, and ultrasound features can be used as a potential imaging index to provide important information for the precise diagnosis and treatment of breast cancer.

Imaging of Fiber Waviness in Thick Composites with Unknown Material Properties Using Probability-Based Ultrasound Non-Reciprocity.

Fiber waviness and voids may be produced in thick composites due to improper manufacturing conditions and consequently pose a risk of structural failure. A proof-of-concept solution for imaging fiber waviness in thick porous composites was proposed from both numerical and experimental studies, via calculating ultrasound non-reciprocity along different wave paths in a sensing network constructed by two phased array probes. Time-frequency analyses were conducted to reveal the cause of ultrasound non-reciprocity in wavy composites. Subsequently, the number of elements in the probes and excitation voltages was determined for fiber waviness imaging using the ultrasound non-reciprocity with a probability-based diagnostic algorithm. The fiber angle gradient was observed to cause ultrasound non-reciprocity and fiber waviness in the thick wavy composites were successfully imaged regardless of presence of voids. This study proposes a new feature for the ultrasonic imaging of fiber waviness and is expected to contribute to processing improvement in thick composites without prior knowledge of material anisotropy.

THE USE OF ULTRASOUND TOMOGRAPHY TO IMPROVE ULTRASOUND CONTROL EFFICIENCY

To ensure safe and reliable operation of pipeline systems, it is necessary to regularly carry out work on technical diagnostics. Ultrasonic inspection is one of the most common methods for pipeline technical condition determining. It has many advantages over other control methods among which there can be distinguished accessibility, the absence of additional requirements for equipping the object under examination, the absence of an impact on the object of control itself, and safety. But ultrasonic inspection also has disadvantages some of which can be eliminated by using an individual piezo elements of multi-element transducer instead of simple single-element transducers.&#x0D; The method of pipeline wall thickness determining using piezo elements of a multi-element transducer, as well as searching for and identifying the type and size of the defect, is known as ultrasonic tomography.&#x0D; This paper presents the main features of the transducers used in ultrasonic tomography, possibilities of ultrasonic tomography when it is used in field pipeline diagnostics. The advantages of using the method of ultrasonic tomography in comparison with conventional ultrasonic control are considered.