Ultrasonic Imaging Research Articles

Use of deep learning and data augmentation by physics-based modelling for crack characterisation from multimodal ultrasonic TFM images

Use of deep learning and data augmentation by physics-based modelling for crack characterisation from multimodal ultrasonic TFM images

Defect classification of composite materials using transfer learning methods

ABSTRACT Nowadays, composite materials have become prevalent across various sectors, particularly finding usage in large-scale applications such as spaceships, automobiles, and aircrafts. The accurate detection of the defects in these materials is crucial, yet traditional methods often rely on human inspection, which is susceptible to errors. Recent advancements in machine learning have enabled defect detection using ultrasonic non-destructive testing methods. This paper introduces a new dataset named UNDT, which is obtained from the scans of 60 different composite materials, generating a total of 1150 images depicting both defective and non-defective areas. Several transfer learning methods are applied on the newly introduced UNDT dataset as well as the publicly available USimgAIST ultrasonic dataset. Comparative performance assessments illustrate the significance of utilising the transfer learning approach for defect classification on ultrasonic inspection images. Furthermore, the research emphasises the substantial benefits of employing these transfer learning methods. Notably, the DenseNet121 and VGG19 models achieve the highest accuracy rates, with 98.8% and 98.6% on the UNDT and USimgAIST datasets, respectively.

Ultrasonic Image Characteristics of Palatine Tonsils in Healthy Children and Analysis of Factors Influencing Image Quality.

To explore the ultrasonic image characteristics of palatine tonsils in healthy children and the factors affecting image quality. A total of 750 images of palatine tonsils were collected from 375 healthy children. According to ultrasonic image quality, the images were divided into three groups. Both systemic and local factors were analyzed among the different groups. The palatine tonsils showed quasi-circular or flat oval, low echo or light and dark band arrangement, a striped medium echo, and a clear boundary. Age, height, weight, body mass index, body surface area, distance from the skin to the posterior margin of the tonsils, thickness of the anterior soft tissue of the tonsils, and thickness of the anterior submandibular gland of the tonsils were significantly different among the different image quality groups (p < 0.05). Multivariate logistic regression analyses revealed that height, weight, thickness of the anterior soft tissue of the tonsils, and thickness of the anterior submandibular gland of the tonsils were independent factors affecting the quality of the ultrasonic images of the palatine tonsils. There are characteristic ultrasonic image manifestations of the palatine tonsils. Tonsil ultrasound image quality is affected by individual and local factors.

Fast and Smart State Characterization of Large-Format Lithium-Ion Batteries via Phased-Array Ultrasonic Sensing Technology.

Lithium-ion batteries (LIBs) are widely used in electric vehicles and energy storage systems, making accurate state transition monitoring a key research topic. This paper presents a characterization method for large-format LIBs based on phased-array ultrasonic technology (PAUT). A finite element model of a large-format aluminum shell lithium-ion battery is developed on the basis of ultrasonic wave propagation in multilayer porous media. Simulations and comparative analyses of phased array ultrasonic imaging are conducted for various operating conditions and abnormal gas generation. A 40 Ah ternary lithium battery (NCMB) is tested at a 0.5C charge-discharge rate, with the state of charge (SOC) and ultrasonic data extracted. The relationship between ultrasonic signals and phased array images is established through simulation and experimental comparisons. To estimate the SOC, a fully connected neural network (FCNN) model is designed and trained, achieving an error of less than 4%. Additionally, phased array imaging, which is conducted every 5 s during overcharging and overdischarging, reveals that gas bubbles form at 0.9 V and increase significantly at 0.2 V. This research provides a new method for battery state characterization.

Highly Sensitive Phased Array Probes based on Capacitive Micromachined Ultrasonic Transducers

Capacitive Micromachined Ultrasonic Transducers (CMUTs) offer a wide freedom of design for ultrasonic phased arrays. They are characterized, in comparison to piezoelectric transducers, by a higher sensitivity in receiving and a wider bandwidth based on their physical properties. Especially in combination with integrated preamplifiers the high receiving sensitivity compensates or rather overcompensates the lower transmission power of the CMUT in single probe applications with pulse-echo technique. This asymmetric behavior opens new opportunities in the application. In medical diagnostics it allows to meet the maximum permissible ultrasonic radiation force with the best sensitivity. In nondestructive testing the transmission power can be increased by the combination of a piezoelectric probe for transmitting and a CMUT probe for receiving. Especially in double probe techniques, such as pitch-catch or time-of-flight diffraction (TOFD), this is an efficient extension of the conventional approach with two piezoelectric transducers. The CMUT array probes developed by Fraunhofer IPMS with integrated preamplifier and bias voltage converter powered by a standard USB-A connector can be applied as one to one substitute for piezoelectric phased arrays with commercially available ultrasonic devices without adaption or additional electronics. The CMUT arrays are best suited for immersion technique and medical sonography because of their natural matching to water-like materials. They are applicable as well for solid surfaces with a special coating. We present the first results of ultrasonic imaging with our CMUT array probes in comparison with a commercially available piezoelectric phased array probe.

High-Resolution In Situ Ultrasonic Imaging Platform for Studying Localized Corrosion Morphology

High-Resolution In Situ Ultrasonic Imaging Platform for Studying Localized Corrosion Morphology

Comparative Study on NDT Techniques for Evaluation of Concrete Quality Exposed to Marine Environment

Concrete, the primary material used in quay walls, is directly exposed to saline environments. Coping concrete, particularly in areas where periodic berthing and loading/unloading occur, is prone to rapid quality deterioration. Current facility safety and maintenance guidelines assess concrete durability at specific points through sampling, which are intended to represent the entire inspection unit. This paper explores quality management strategies from an areal perspective by applying various non-destructive scanning methods to extensive areas of coping concrete. Ultrasonic array imaging and ground-penetrating radar scanning images revealed significant quality degradation in berthing operation areas, whereas sampling-based ultrasonic pulse velocity and rebound hardness values were less effective in detecting this degradation.

In-situ detection of electrolyte defects in lithium-ion batteries using ultrasonic imaging and analysis of formation patterns

The urgent necessity for enhanced cycling performance in lithium batteries is paramount for electric vehicles to attain broader economic advantages. However, prolonged usage and cycling often lead to electrolyte de-wetting within the battery, posing a significant risk to battery safety and lifespan reduction. A thorough understanding of the mechanisms underlying electrolyte de-wetting is pivotal for the development of long-lasting batteries. This study employs an ultrasonic non-destructive testing method to investigate changes in the internal electrolyte during battery operation. Analysis of the results found that during to the relatively higher current density and temperature near the tabs, electrolyte de-wetting is more prone to occur in these areas, with defects being more severe at the positive electrode compared to the negative electrode. Finally, these issues are addressed to provide reasonable recommendations for future battery design and optimization.

Application of ultrasonic imaging technology in beef cattle breeding management

ObjectiveThe aim of this study was to explore in depth the application of ultrasonic imaging technology in beef cattle reproduction management in order to improve the efficiency and management of beef cattle reproduction. MethodsIn this study, ultrasonographic diagnostic techniques were used to follow up the follicles and corpus luteum in the uterus and ovaries of dairy cows at different stages of development as well as at different periods of gestation of dairy cows, and to detect the effects of different fattening conditions of the cows and the number of litters on the sitting rate. ResultsThe diameter of mature follicles was generally around 16 mm, and the majority of them were 11–20 mm in diameter. Ultrasonography was used to detect early pregnancy in cows at 33–55 d. Ultrasound was used to identify the sex of the foetus most easily at 70–80 d. The results of this study showed that the sex of the foetus was most easily identified in cows at 70–80 d. The fat of the cow and the number of births also had a significant impact on pregnancy rates. ConclusionUltrasound imaging technology has an important application value in the management of beef cattle reproduction, and in pregnancy detection, it can achieve early and accurate diagnosis, improve the accuracy of detection, and differentiate between heifers in estrus and pregnant heifers. In addition, it can also be used for foetal sex identification at a specific period of time, providing a basis for breeding programmes.

Ultrasound for breast cancer detection: A bibliometric analysis of global trends between 2004 and 2024.

With the advancement of computer technology and imaging equipment, ultrasound has emerged as a crucial tool in breast cancer diagnosis. To gain deeper insights into the research landscape of ultrasound in breast cancer diagnosis, this study employed bibliometric methods for a comprehensive analysis spanning from 2004 to 2024, analyzing 3523 articles from 2176 institutions in 82 countries/regions. Over this period, publications on ultrasound diagnosis of breast cancer showed a fluctuating growth trend from 2004 to 2024. Notably, China, Seoul National University and Kim EK emerged as leading contributors in ultrasound for breast cancer detection, with the most published and cited journals being Ultrasound Med Biol and Radiology. The research spots in this area included "breast lesion", "dense breast" and "breast-conserving surgery", while "machine learning", "ultrasonic imaging", "convolutional neural network", "case report", "pathological complete response", "deep learning", "artificial intelligence" and "classification" are anticipated to become future research frontiers. This groundbreaking bibliometric analysis and visualization of ultrasonic breast cancer diagnosis publications offer clinical medical professionals a reliable research focus and direction.

Study on non-destructive visualization identification of concrete internal cracks based on SH array ultrasound

Ultrasonic nondestructive testing (NDT) technology was one of the most frequently used and fastest-developing NDT techniques in detection field. This method had high detection sensitivity, more accurate defect localization, and was harmless to the human body. With the development of ultrasonic testing technology, modern ultrasonic imaging technology generally had automatic data acquisition and processing functions, which allowed for intuitive and clear recognition of internal defects by the human eyes. The overall purpose of this study was to visualize the cracks in concrete by synthetic aperture focusing technique (SAFT) and full-waveform inversion (FWI) algorithms on the basis of ultrasonic nondestructive testing technology. At present, there have been studies on the use of ultrasonic instruments to detect the internal defects of concrete. However, the accuracy and authenticity of this method have not been compared in previous studies. Therefore, in this experiment, four concrete specimens with different buried depths, angles, shapes, and thicknesses of cracks were designed. Based on SH ultrasonic wave NDT technology, two types of operations were performed on the collected ultrasonic wave data: one was the application of SAFT method, and the other was the first application of FWI method for detecting internal cracks in concrete. The study found that both algorithms were most accurate in determining the burial depth of cracks, with error results not exceeding 10 %. They also showed good recognition effects for the angle, shape, and thickness of the buried cracks. This proved that both identification methods had the capability to recognize internal cracks. The Introview software bundled with the ultrasonic instrument could identify cracks using SAFT directly and quickly. When FWI was used with MATLAB computation, the results were more precise and intuitive. The overall purpose of this study was to detect cracks in concrete by SAFT and FWI algorithms on the basis of ultrasonic nondestructive testing technology. Combining the two crack identification techniques could be of great significance for ensuring the long-term safety and stability of concrete structures, providing strong support for structural maintenance and reinforcement.

Optimization and Application Analysis of Phase Correction Method Based on Improved Image Registration in Ultrasonic Image Detection

ABSTRACTIn order to prevent and detect a wide range of disorders, including those of the brain, thoracic, digestive, urogenital, and cardiovascular systems, ultrasound technology is essential for assessing physiological data and tissue morphology. Its capacity to deliver real‐time, high‐frequency scans makes it a handy and non‐invasive diagnostic tool. However, issues like patient movements and probe jitter from human error can provide a large amount of interference, resulting in inaccurate test findings. Techniques for image registration can assist in locating and eliminating unwanted interference while maintaining crucial data. Even though there has been research on improving these techniques in Matlab, there are no specialized systems for interference removal, and the procedure is still time‐consuming, particularly when working with huge quantities of ultrasound images. The phase correlation technique, which converts images into the frequency domain and makes noise suppression easier, is one of the most efficient algorithms now in use since it can tolerate noise with resilience. Nevertheless, little research has been done on using this technique to identify displacement in blood vessel wall ultrasound images. To address these gaps, this work presents an image registration system that uses the phase correlation algorithm. The system provides rotation, zoom registration, picture translation, and displacement detection of the vessel wall in addition to interference removal. Furthermore, batch processing is included to increase the effectiveness of registering multiple ultrasound pictures. Through efficient interference management and streamlined registration, this method offers a workable way to improve the precision and efficacy of ultrasonic diagnostics.

Generation of bessel-like beam by a binary ultrasonic lens

Bessel beams have already been used in acoustic tweezers, ultrasonic medical imaging, and Doppler velocity estimation due to their non-diffractive and self-healing properties. We proposed a binary ultrasonic lens, with ultra-thin planar periodic structures for efficient conversion of the plane wave into a Bessel-like beam. The effectiveness of long-axis focusing has been demonstrated through simulations and experiments with FWHM of 8.5 mm and 9.5 mm around 10 mm. By varying the operating frequency of the incident wave from 1.9 MHz to 2.2 MHz, the position of the long-axis focusing point can be adjusted experimentally from 23.05 mm to 28.95 mm. Additionally, the beam generated by the binary ultrasonic lens can form a focused sound field when passing through multi-layered tissues and the self-healing capability of the Bessel-like beam has been numerically validated, showing strong robustness. This binary ultrasonic lens for a Bessel-like beam would conform better to ergonomic and miniaturization requirements, and expand versatile applications in clinical diagnosis and therapy.

Investigating the Internal Deterioration of the Auriga Statue of Mozia Island, Sicily, through Ultrasonic and Ground-Penetrating Radar Studies

The Greek marble statue of the Auriga of Mozia Island, in Sicily, is the most important artwork displayed at the Whitaker Foundation Archaeological Museum. It underwent geophysical investigations twice, in 2012 and 2021, to assess the marble’s degradation. The 2012 investigation prepared the statue for transfer to the Paul Getty Museum in New York and repositioning on an anti-seismic pedestal. The 2021 investigation evaluated potential new damage before another transfer. Both investigations utilized 3D ultrasonic tomography (UST) to detect degraded marble areas and ground-penetrating radar (GPR) to identify internal discontinuities, such as fractures or lesions, and locate metal pins that were previously inserted to reassemble the statue and its pedestal. Results from the UST indicate an average marble velocity of approximately 4700 m/s, suggesting good mechanical strength, with some areas showing lower velocities (~3000 m/s) within the material’s variability range. The GPR profiles demonstrated internal signal homogeneity, excluding internal fracture surfaces or lesions, and confirmed the presence of metallic pins. This study highlights the effectiveness of integrating UST and GPR for non-invasive diagnostics of marble sculptures, providing detailed insights into the marble’s condition and identifying hidden defects or damage.

Prediction of lateral neck metastasis in patients with papillary thyroid cancer with suspicious lateral lymph ultrasonic imaging based on central lymph node metastasis features.

Neck lymphatic metastasis is a common occurrence with thyroid cancers, and pre operative lateral lymph node metastasis (LLNM) and postoperative lateral lymph node recurrence (LLNR) are two independent risk factors that are negatively associated with the prognosis of patients with thyroid cancer. The aim of the present study was to investigate the relationship between central lymph node metastasis (CLNM) and LLNM in patients with papillary thyroid carcinoma (PTC) with sonographically suspected LLNM, such as those without lymph node fine-needle aspiration (FNA) cytological results or negative FNA results at the time of diagnosis. The predictive ability of CLNM regarding LLNR was also investigated. The present study retrospectively reviewed the clinical data of 1,061 patients that were surgically treated for PTC and 128 patients with sonographically suspected lateral lymph nodes that received central lymph node dissection and lateral lymph node dissection at the Thyroid Department of The First Affiliated Hospital of Anhui Medical University (Hefei, China) from June 2019 to June 2021. In patients with suspicious ultrasonic images suggesting LLNM, a significant association between the central lymph node ratio (CLNR), the number of positive central lymph nodes and LLNM was demonstrated. Otherwise, there were no statistically significant differences between the CLNR in patients with PTC and patients with PTC without evidence of lateral cervical metastasis. However, the rate of LLNR increased significantly when the number of positive central lymph nodes was >3. In conclusion, the CLNR and the number of positive central lymph nodes could be used to predict LLNM in patients with PTC with sonographically suspect lateral lymph nodes, including those with no FNA cytological results or negative FNA results, which may potentially support physicians in making personalized clinical decisions.

Enhancing ultrasonic attenuation images through multi-frequency coupling with total nuclear variation.

Quantitative ultrasound is a non-invasive image modality that numerically characterizes tissues for medical diagnosis using acoustical parameters, such as the attenuation coefficient slope. A previous study introduced the total variation spectral log difference (TVSLD) method, which denoises spectral log ratios on a single-channel basis without inter-channel coupling. Therefore, this work proposes a multi-frequency joint framework by coupling information across frequency channels exploiting structural similarities among the spectral ratios to increase the quality of the attenuation images. A modification based on the total nuclear variation (TNV) was considered. Metrics were compared to the TVSLD method with simulated and experimental phantoms and two samples of fibroadenoma in vivo breast tissue. The TNV demonstrated superior performance, yielding enhanced attenuation coefficient slope maps with fewer artifacts at boundaries and a stable error. In terms of the contrast-to-noise ratio enhancement, the TNV approach obtained an average percentage improvement of 34% in simulation, 38% in the experimental phantom, and 89% in two in vivo breast tissue samples compared to TVSLD, showing potential to enhance visual clarity and depiction of attenuation images.

Ultrasound-mediated PLGA-PEI Nanobubbles Carrying STAT6 SiRNA Enhances NSCLC Treatment via Repolarizing Tumor-associated Macrophages from M2 to M1 Phenotypes.

Tumor-associated macrophages (TAMs) are crucial for non-small cell lung cancer (NSCLC) development. In this study, polylactic acid-co-glycolic acid (PLGA)-polyethylenimine (PEI) nanobubbles (NBs) carrying STAT6 siRNA were prepared and combined with ultrasound-mediated nanobubbles destruction (UMND) to silence the STAT6 gene, ultimately repolarizing TAMs from the M2 to the M1 phenotype, treating NSCLC in vitro. PLGA-PEI NBs-siRNA were prepared and characterised, and their respective ultrasound imaging, biological stabilities and cytotoxicities were detected. Transfection efficiency was evaluated by fluorescence microscopy and flow cytometry. Repolarization of THP-1-derived M2-like macrophages was determined by qPCR and flow cytometry. NSCLC cells (A549) were co-cultured with transfected M2-like macrophages or their associated conditioned medium (CM). Western blotting was used to detect STAT6 gene silencing in M2-like macrophages and markers of epithelial and mesenchymal in A549 cells. The proliferation of A549 cells was detected using CCK-8 and cell colony formation assays. Transwell assays were used to detect the migration and invasion of A549 cells. PLGA-PEI NBs-siRNA had an average size of 223.13 ± 0.92 nm and a zeta potential of about -5.59 ± 0.97 mV. PLGA-PEI NBs showed excellent ultrasonic imaging capability in addition to biological stability to protect siRNA from degradation. UMND enhanced PLGA-PEI NBs-STAT6 siRNA transfection in M2-like macrophages, which made M2-like macrophages repolarize to M1-like macrophages and prevented proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) in A549 cells. UMND enhanced PLGA-PEI NBs-STAT6 siRNA to repolarize TAMs from the M2 to the M1 phenotype, thus treating NSCLC. These findings provide a promising therapeutic approach for enhancing NSCLC immunotherapy.

Design and Evaluation of a Weighted Periodic Sparse Array for Low-Complexity 1-D Phased Array Ultrasound Imaging Systems.

A sparse array offers a significant reduction in the complexity of ultrasonic imaging systems by decreasing the number of active elements and associated electrical circuits needed to form a focused beam. Consequently, for 1-D arrays, it has been adopted in the development of miniaturized systems such as portable, handheld, or smartphone-based systems. Previously, we developed an analytic method that can design a pair of 1-D periodic sparse arrays (PSAs) satisfying three specific constraints, which are the array size, desired grating lobe level, and sparseness factor (SF). In this study, we further developed our method by incorporating aperture weighting functions, which take the form of tapered rectangular functions to introduce null points on the beam pattern. These null points effectively suppress grating lobes generated by a matching pair of arrays. The design process commences with determining transmit and receive PSA patterns, followed by deriving corresponding aperture weighting functions. First, aperture functions of a base and weighting arrays are convolved, which is then upsampled to the targeted array size. Finally, the upsampled aperture is convolved to an aperture function of a subarray, resulting in weighted PSAs (wPSAs). Pulsed wave (PW) simulation confirmed improved grating lobe suppression with wPSAs compared to PSAs. Phantom imaging experiments using a 1-D phased array validated the enhanced contrast due to suppressed grating lobes but at the cost of small degradation in lateral resolution. The signal-to-noise ratio (SNR) also gradually declined with the greater SFs, but no significant difference in SNR was observed between wPSAs and PSAs. Finally, in vivo echocardiography imaging highlighted the clinical potential of wPSAs, particularly with high SFs. Overall, these results suggest that wPSAs can effectively enhance contrast compared to PSAs under the given SF or, alternatively, wPSA with greater SFs can achieve comparable image quality to PSAs with lower SFs. In conclusion, the wPSA approach holds promise for further reducing the complexity of ultrasound imaging systems.

Ultracompact all-fiber self-transceiving ultrasonic probe with an enhanced working distance.

All-optical ultrasonic probes exhibit notable benefits in ultrasonic detection and imaging. Typically, two separate optical fibers are used for excitation and detection, yet limited research has explored the integration of both functionalities within a single fiber. In this Letter, to our knowledge, a new method for fabricating an all-fiber self-transceiving ultrasonic probe is proposed with a lateral dimension of less than 500 µm. Double cladding fiber (DCF) is spliced with a short segment of thin-diameter single-mode fiber (TDSMF), which is then embedded into a fiber bubble to form a Fabry-Perot cavity, and the bubble surface is coated with a composite material layer. The pulsed laser propagates through the inner cladding of DCF and leaks from the splicing point of DCF-TDSMF, inducing the material excitation for efficient ultrasound generation. The core-guided detection laser is directed to the TDSMF end, entering the bubble microcavity and inducing an optical interference for weak echo detection. The emitting functionality produces an ultrasound with a -6 dB bandwidth of 17.5 MHz and a peak frequency of 6.29 MHz, which is well-matched with the fiber microcavity's response frequency of 3.29 MHz. Through self-transceiving experiments, low-noise pulse-echo signals are captured at varying working distances of up to 3.78 cm. The proposed probe exhibits great potential in biomedical and industrial fields due to its all-fiber miniaturization and enhanced-distance detection capability.

Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

Temperature prediction is crucial in the clinical ablation treatment of liver cancer, as it can be used to estimate the coagulation zone of microwave ablation. Experiments were conducted on 83 fresh ex vivo porcine liver tissues at two ablation powers of 15 W and 20 W. Ultrasound grayscale images and temperature data from multiple sampling points were collected. The machine learning method of random forests was used to train the selected texture features, obtaining temperature prediction models for sampling points and the entire ultrasound imaging area. The accuracy of the algorithm was assessed by measuring the area of the hyperechoic area in the porcine liver tissue cross-section and ultrasound grayscale images. The model exhibited a high degree of accuracy in temperature prediction and the identification of coagulation zone. Within the test sets for the 15 W and 20 W power groups, the average absolute error for temperature prediction was 1.14°C and 4.73°C, respectively. Notably, the model's accuracy in measuring the area of coagulation was higher than that of traditional ultrasonic grey-scale imaging, with error ratios of 0.402 and 0.182 for the respective power groups. Additionally, the model can filter out texture features with a high correlation to temperature, providing a certain degree of interpretability. The temperature prediction model proposed in this study can be applied to temperature monitoring and coagulation zone range assessment in microwave ablation.