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Keywords = ultrasound backscattered signals

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16 pages, 13319 KiB  
Article
Research on Acoustic Field Correction Vector-Coherent Total Focusing Imaging Method Based on Coarse-Grained Elastic Anisotropic Material Properties
by Tianwei Zhao, Ziyu Liu, Donghui Zhang, Junlong Wang and Guowen Peng
Sensors 2025, 25(15), 4550; https://doi.org/10.3390/s25154550 - 23 Jul 2025
Viewed by 217
Abstract
This study aims to address the challenges posed by uneven energy amplitude and a low signal-to-noise ratio (SNR) in the total focus imaging of coarse-crystalline elastic anisotropic materials. A novel method for acoustic field correction vector-coherent total focus imaging, based on the materials’ [...] Read more.
This study aims to address the challenges posed by uneven energy amplitude and a low signal-to-noise ratio (SNR) in the total focus imaging of coarse-crystalline elastic anisotropic materials. A novel method for acoustic field correction vector-coherent total focus imaging, based on the materials’ properties, is proposed. To demonstrate the effectiveness of this method, a test specimen, an austenitic stainless steel nozzle weld, was employed. Seven side-drilled hole defects located at varying positions and depths, each with a diameter of 2 mm, were examined. An ultrasound simulation model was developed based on material backscatter diffraction results, and the scattering attenuation compensation factor was optimized. The acoustic field correction function was derived by combining acoustic field directivity with diffusion attenuation compensation. The phase coherence weighting coefficients were calculated, followed by image reconstruction. The results show that the proposed method significantly improves imaging amplitude uniformity and reduces the structural noise caused by the coarse crystal structure of austenitic stainless steel. Compared to conventional total focus imaging, the detection SNR of the seven defects increased by 2.34 dB to 10.95 dB. Additionally, the defect localization error was reduced from 0.1 mm to 0.05 mm, with a range of 0.70 mm to 0.88 mm. Full article
(This article belongs to the Special Issue Ultrasound Imaging and Sensing for Nondestructive Testing)
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17 pages, 4901 KiB  
Article
Optimization of High-Frequency Ultrasound Imaging to Detect Incremental Changes in Mineral Content at the Cartilage–Bone Interface Ex Vivo
by Akshay Charan, Parag V. Chitnis and Caroline D. Hoemann
Biomimetics 2025, 10(3), 160; https://doi.org/10.3390/biomimetics10030160 - 5 Mar 2025
Viewed by 825
Abstract
(1) Background: Osteoarthritis is a degenerative disease of the whole joint marked by cartilage–bone interface (CBI) remodeling, but methods to monitor subtle changes in mineralization are lacking. We optimized a non-destructive ultrasound imaging method to monitor incremental shifts in mineralization, using brief decalcification [...] Read more.
(1) Background: Osteoarthritis is a degenerative disease of the whole joint marked by cartilage–bone interface (CBI) remodeling, but methods to monitor subtle changes in mineralization are lacking. We optimized a non-destructive ultrasound imaging method to monitor incremental shifts in mineralization, using brief decalcification as a mimetic of CBI remodeling. (2) Methods: We used a 35-MHz transducer to scan 3 mm diameter bovine osteochondral explants wrapped with parafilm to produce surface-directed decalcification and dedicated 3D-printed holders to maintain sample orientation. Customized MATLAB codes and a matched pair design were used for quantitative hypothesis testing. (3) Results: Optimal scan precision was obtained when the High-Frequency Ultrasound (HFUS) focal distance was trained at the CBI. HFUS cartilage thickness increased by 53 ± 21 µm or 97 ± 28 µm after three or seven hours of ethylene diamine tetra-acetic acid (EDTA) (but not PBS), respectively, and was highly correlated with histological cartilage thickness (R = 0.98). The en face CBI backscatter pattern was irregular and shifted after the EDTA-displacement of the mineral front. Collective data suggested that the −10 dB echogenic CBI signal originated from the mineral front and varied topographically with undulating mineral thickness. (4) Conclusions: This imaging approach could be used to monitor tidemark remodeling in live explant cultures, toward identifying new treatments that inhibit tidemark advancement and slow osteoarthritis progression. Full article
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19 pages, 4867 KiB  
Article
Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study
by Haiming Ai, Yong Huang, Dar-In Tai, Po-Hsiang Tsui and Zhuhuang Zhou
Sensors 2024, 24(17), 5513; https://doi.org/10.3390/s24175513 - 26 Aug 2024
Cited by 2 | Viewed by 1959
Abstract
The early detection of liver fibrosis is of significant importance. Deep learning analysis of ultrasound backscattered radiofrequency (RF) signals is emerging for tissue characterization as the RF signals carry abundant information related to tissue microstructures. However, the existing methods only used the time-domain [...] Read more.
The early detection of liver fibrosis is of significant importance. Deep learning analysis of ultrasound backscattered radiofrequency (RF) signals is emerging for tissue characterization as the RF signals carry abundant information related to tissue microstructures. However, the existing methods only used the time-domain information of the RF signals for liver fibrosis assessment, and the liver region of interest (ROI) is outlined manually. In this study, we proposed an approach for liver fibrosis assessment using deep learning models on ultrasound RF signals. The proposed method consisted of two-dimensional (2D) convolutional neural networks (CNNs) for automatic liver ROI segmentation from reconstructed B-mode ultrasound images and one-dimensional (1D) CNNs for liver fibrosis stage classification based on the frequency spectra (amplitude, phase, and power) of the segmented ROI signals. The Fourier transform was used to obtain the three kinds of frequency spectra. Two classical 2D CNNs were employed for liver ROI segmentation: U-Net and Attention U-Net. ROI spectrum signals were normalized and augmented using a sliding window technique. Ultrasound RF signals collected (with a 3-MHz transducer) from 613 participants (Group A) were included for liver ROI segmentation and those from 237 participants (Group B) for liver fibrosis stage classification, with a liver biopsy as the reference standard (Fibrosis stage: F0 = 27, F1 = 49, F2 = 51, F3 = 49, F4 = 61). In the test set of Group A, U-Net and Attention U-Net yielded Dice similarity coefficients of 95.05% and 94.68%, respectively. In the test set of Group B, the 1D CNN performed the best when using ROI phase spectrum signals to evaluate liver fibrosis stages ≥F1 (area under the receive operating characteristic curve, AUC: 0.957; accuracy: 89.19%; sensitivity: 85.17%; specificity: 93.75%), ≥F2 (AUC: 0.808; accuracy: 83.34%; sensitivity: 87.50%; specificity: 78.57%), and ≥F4 (AUC: 0.876; accuracy: 85.71%; sensitivity: 77.78%; specificity: 94.12%), and when using the power spectrum signals to evaluate ≥F3 (AUC: 0.729; accuracy: 77.14%; sensitivity: 77.27%; specificity: 76.92%). The experimental results demonstrated the feasibility of both the 2D and 1D CNNs in liver parenchyma detection and liver fibrosis characterization. The proposed methods have provided a new strategy for liver fibrosis assessment based on ultrasound RF signals, especially for early fibrosis detection. The findings of this study shed light on deep learning analysis of ultrasound RF signals in the frequency domain with automatic ROI segmentation. Full article
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20 pages, 9175 KiB  
Review
Ultrasound Imaging in Knee Osteoarthritis: Current Role, Recent Advancements, and Future Perspectives
by Valerio D’Agostino, Angela Sorriento, Andrea Cafarelli, Danilo Donati, Nicolas Papalexis, Alessandro Russo, Gina Lisignoli, Leonardo Ricotti and Paolo Spinnato
J. Clin. Med. 2024, 13(16), 4930; https://doi.org/10.3390/jcm13164930 - 21 Aug 2024
Cited by 17 | Viewed by 6443
Abstract
While conventional radiography and MRI have a well-established role in the assessment of patients with knee osteoarthritis, ultrasound is considered a complementary and additional tool. Moreover, the actual usefulness of ultrasound is still a matter of debate in knee osteoarthritis assessment. Despite that, [...] Read more.
While conventional radiography and MRI have a well-established role in the assessment of patients with knee osteoarthritis, ultrasound is considered a complementary and additional tool. Moreover, the actual usefulness of ultrasound is still a matter of debate in knee osteoarthritis assessment. Despite that, ultrasound offers several advantages and interesting aspects for both current clinical practice and future perspectives. Ultrasound is potentially a helpful tool in the detection of anomalies such as cartilage degradation, osteophytes, and synovitis in cases of knee osteoarthritis. Furthermore, local diagnostic and minimally invasive therapeutic operations pertaining to knee osteoarthritis can be safely guided by real-time ultrasound imaging. We are constantly observing a growing knowledge and awareness among radiologists and other physicians, concerning ultrasound imaging. Ultrasound studies can be extremely useful to track the response to various therapies. For this specific aim, tele-ultrasonography may constitute an easy tool aiding precise and repeated follow-up controls. Moreover, raw radio-frequency data from US backscattering signals contain more information than B-mode imaging. This paves the way for quantitative in-depth analyses of cartilage, bone, and other articular structures. Overall, ultrasound technologies and their rapid evolution have the potential to make a difference at both the research and clinical levels. This narrative review article describes the potential of such technologies and their possible future implications. Full article
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16 pages, 3461 KiB  
Article
High-Resolution Ultrasound Platform for Infant Meningitis Detection: An In Vitro Demonstration
by Manuel Navarrete, David Castells-Rufas, Hassane Baghdad Kichou, Guillermo Navarro-Patron, Javier Jimenez and Jordi Carrabina
Sensors 2024, 24(15), 4768; https://doi.org/10.3390/s24154768 - 23 Jul 2024
Cited by 1 | Viewed by 1666
Abstract
Infant meningitis remains a severe burden on global health, particularly for young infants. Traditional ultrasound imaging techniques are limited in spatial resolution to visualize white blood cells (WBCs) in the cerebrospinal fluid (CSF), which is considered a well-established marker for meningitis detection. This [...] Read more.
Infant meningitis remains a severe burden on global health, particularly for young infants. Traditional ultrasound imaging techniques are limited in spatial resolution to visualize white blood cells (WBCs) in the cerebrospinal fluid (CSF), which is considered a well-established marker for meningitis detection. This work presents a novel platform that uses high-resolution ultrasound to detect the backscatter signals from microscopic CSF WBCs through the anterior fontanelle of neonates and young infants. The whole system was built around a custom probe that allows for a 20 MHz focused transducer to be mechanically controlled to map the area of interest in the CSF. Data processing can be performed internally in the device without the need to extract the images for further analysis. The in vitro feasibility of the proposed solution was evaluated in imaging 7 μm particle suspensions at different concentrations relevant to meningitis diagnosis ranging from 7- to 646-particles (pp)/μL. The experimental tests were conducted from a simple setup using a sample container to a more realistic setup based on an anatomical phantom of the neonatal head. The results show high-quality images, where 7 μm particles can be resolved for the different concentrations. Full article
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13 pages, 4963 KiB  
Article
Ultrasound Entropy Imaging Based on the Kernel Density Estimation: A New Approach to Hepatic Steatosis Characterization
by Ruiyang Gao, Po-Hsiang Tsui, Shuicai Wu, Dar-In Tai, Guangyu Bin and Zhuhuang Zhou
Diagnostics 2023, 13(24), 3646; https://doi.org/10.3390/diagnostics13243646 - 12 Dec 2023
Cited by 3 | Viewed by 1522
Abstract
In this paper, we present the kernel density estimation (KDE)-based parallelized ultrasound entropy imaging and apply it for hepatic steatosis characterization. A KDE technique was used to estimate the probability density function (PDF) of ultrasound backscattered signals. The estimated PDF was utilized to [...] Read more.
In this paper, we present the kernel density estimation (KDE)-based parallelized ultrasound entropy imaging and apply it for hepatic steatosis characterization. A KDE technique was used to estimate the probability density function (PDF) of ultrasound backscattered signals. The estimated PDF was utilized to estimate the Shannon entropy to construct parametric images. In addition, the parallel computation technique was incorporated. Clinical experiments of hepatic steatosis were conducted to validate the feasibility of the proposed method. Seventy-two participants and 204 patients with different grades of hepatic steatosis were included. The experimental results show that the KDE-based entropy parameter correlates with log10 (hepatic fat fractions) measured by magnetic resonance spectroscopy in the 72 participants (Pearson’s r = 0.52, p < 0.0001), and its areas under the receiver operating characteristic curves for diagnosing hepatic steatosis grades ≥ mild, ≥moderate, and ≥severe are 0.65, 0.73, and 0.80, respectively, for the 204 patients. The proposed method overcomes the drawbacks of conventional histogram-based ultrasound entropy imaging, including limited dynamic ranges and histogram settings dependence, although the diagnostic performance is slightly worse than conventional histogram-based entropy imaging. The proposed KDE-based parallelized ultrasound entropy imaging technique may be used as a new ultrasound entropy imaging method for hepatic steatosis characterization. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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14 pages, 3334 KiB  
Article
Nonlinear Ultrasonic Imaging for Porosity Evaluation
by Mario Emanuele De Simone, Salvatore Boccardi, Gian Piero Malfense Fierro and Michele Meo
Sensors 2023, 23(14), 6319; https://doi.org/10.3390/s23146319 - 12 Jul 2023
Cited by 2 | Viewed by 2244
Abstract
The influence of porosity on the mechanical behaviour of composite laminates represents a complex problem that involves many variables. Therefore, the evaluation of the type and volume content of porosity in a composite specimen is important for quality control and for predicting material [...] Read more.
The influence of porosity on the mechanical behaviour of composite laminates represents a complex problem that involves many variables. Therefore, the evaluation of the type and volume content of porosity in a composite specimen is important for quality control and for predicting material behaviour during service. A suitable way to evaluate the porosity content in composites is by using nonlinear ultrasonics because of their sensitivity to small cracks. The main objective of this research work is to present an imaging method for the porosity field in composites. Two nonlinear ultrasound techniques are proposed using backscattered signals acquired by a phased array system. The first method was based on the amplitude of the half-harmonic frequency components generated by microbubble reflections, while the second one involved the frequency derivative of the attenuation coefficient, which is proportional to the porosity content in the specimen. Two composite samples with induced porosity were considered in the experimental tests, and the results showed the high accuracy of both methods with respect to a classic C-scan baseline. The attenuation coefficient results showed high accuracy in defining bubble shapes in comparison with the half-harmonic technique when surface effects were neglected. Full article
(This article belongs to the Section Sensing and Imaging)
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21 pages, 3937 KiB  
Review
Skeletal Muscle Assessment Using Quantitative Ultrasound: A Narrative Review
by Aria Ashir, Saeed Jerban, Victor Barrère, Yuanshan Wu, Sameer B. Shah, Michael P. Andre and Eric Y. Chang
Sensors 2023, 23(10), 4763; https://doi.org/10.3390/s23104763 - 15 May 2023
Cited by 24 | Viewed by 7166
Abstract
Ultrasound (US) is an important imaging tool for skeletal muscle analysis. The advantages of US include point-of-care access, real-time imaging, cost-effectiveness, and absence of ionizing radiation. However, US can be highly dependent on the operator and/or US system, and a portion of the [...] Read more.
Ultrasound (US) is an important imaging tool for skeletal muscle analysis. The advantages of US include point-of-care access, real-time imaging, cost-effectiveness, and absence of ionizing radiation. However, US can be highly dependent on the operator and/or US system, and a portion of the potentially useful information carried by raw sonographic data is discarded in image formation for routine qualitative US. Quantitative ultrasound (QUS) methods provide analysis of the raw or post-processed data, revealing additional information about normal tissue structure and disease status. There are four QUS categories that can be used on muscle and are important to review. First, quantitative data derived from B-mode images can help determine the macrostructural anatomy and microstructural morphology of muscle tissues. Second, US elastography can provide information about muscle elasticity or stiffness through strain elastography or shear wave elastography (SWE). Strain elastography measures the induced tissue strain caused either by internal or external compression by tracking tissue displacement with detectable speckle in B-mode images of the examined tissue. SWE measures the speed of induced shear waves traveling through the tissue to estimate the tissue elasticity. These shear waves may be produced using external mechanical vibrations or internal “push pulse” ultrasound stimuli. Third, raw radiofrequency signal analyses provide estimates of fundamental tissue parameters, such as the speed of sound, attenuation coefficient, and backscatter coefficient, which correspond to information about muscle tissue microstructure and composition. Lastly, envelope statistical analyses apply various probability distributions to estimate the number density of scatterers and quantify coherent to incoherent signals, thus providing information about microstructural properties of muscle tissue. This review will examine these QUS techniques, published results on QUS evaluation of skeletal muscles, and the strengths and limitations of QUS in skeletal muscle analysis. Full article
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26 pages, 3904 KiB  
Review
Quantitative Ultrasound Techniques Used for Peripheral Nerve Assessment
by Saeed Jerban, Victor Barrère, Michael Andre, Eric Y. Chang and Sameer B. Shah
Diagnostics 2023, 13(5), 956; https://doi.org/10.3390/diagnostics13050956 - 2 Mar 2023
Cited by 11 | Viewed by 4173
Abstract
Aim: This review article describes quantitative ultrasound (QUS) techniques and summarizes their strengths and limitations when applied to peripheral nerves. Methods: A systematic review was conducted on publications after 1990 in Google Scholar, Scopus, and PubMed databases. The search terms “peripheral nerve”, “quantitative [...] Read more.
Aim: This review article describes quantitative ultrasound (QUS) techniques and summarizes their strengths and limitations when applied to peripheral nerves. Methods: A systematic review was conducted on publications after 1990 in Google Scholar, Scopus, and PubMed databases. The search terms “peripheral nerve”, “quantitative ultrasound”, and “elastography ultrasound” were used to identify studies related to this investigation. Results: Based on this literature review, QUS investigations performed on peripheral nerves can be categorized into three main groups: (1) B-mode echogenicity measurements, which are affected by a variety of post-processing algorithms applied during image formation and in subsequent B-mode images; (2) ultrasound (US) elastography, which examines tissue stiffness or elasticity through modalities such as strain ultrasonography or shear wave elastography (SWE). With strain ultrasonography, induced tissue strain, caused by internal or external compression stimuli that distort the tissue, is measured by tracking detectable speckles in the B-mode images. In SWE, the propagation speed of shear waves, generated by externally applied mechanical vibrations or internal US “push pulse” stimuli, is measured to estimate tissue elasticity; (3) the characterization of raw backscattered ultrasound radiofrequency (RF) signals, which provide fundamental ultrasonic tissue parameters, such as the acoustic attenuation and backscattered coefficients, that reflect tissue composition and microstructural properties. Conclusions: QUS techniques allow the objective evaluation of peripheral nerves and reduce operator- or system-associated biases that can influence qualitative B-mode imaging. The application of QUS techniques to peripheral nerves, including their strengths and limitations, were described and discussed in this review to enhance clinical translation. Full article
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14 pages, 7359 KiB  
Article
Effect of Clutter Filter in High-Frame-Rate Ultrasonic Backscatter Coefficient Analysis
by Masaaki Omura, Kunimasa Yagi, Ryo Nagaoka, Kenji Yoshida, Tadashi Yamaguchi and Hideyuki Hasegawa
Sensors 2023, 23(5), 2639; https://doi.org/10.3390/s23052639 - 27 Feb 2023
Cited by 5 | Viewed by 2465
Abstract
High-frame-rate imaging with a clutter filter can clearly visualize blood flow signals and provide more efficient discrimination with tissue signals. In vitro studies using clutter-less phantom and high-frequency ultrasound suggested a possibility of evaluating the red blood cell (RBC) aggregation by analyzing the [...] Read more.
High-frame-rate imaging with a clutter filter can clearly visualize blood flow signals and provide more efficient discrimination with tissue signals. In vitro studies using clutter-less phantom and high-frequency ultrasound suggested a possibility of evaluating the red blood cell (RBC) aggregation by analyzing the frequency dependence of the backscatter coefficient (BSC). However, in in vivo applications, clutter filtering is required to visualize echoes from the RBC. This study initially evaluated the effect of the clutter filter for ultrasonic BSC analysis for in vitro and preliminary in vivo data to characterize hemorheology. Coherently compounded plane wave imaging at a frame rate of 2 kHz was carried out in high-frame-rate imaging. Two samples of RBCs suspended by saline and autologous plasma for in vitro data were circulated in two types of flow phantoms without or with clutter signals. The singular value decomposition was applied to suppress the clutter signal in the flow phantom. The BSC was calculated using the reference phantom method, and it was parametrized by spectral slope and mid-band fit (MBF) between 4–12 MHz. The velocity distribution was estimated by the block matching method, and the shear rate was estimated by the least squares approximation of the slope near the wall. Consequently, the spectral slope of the saline sample was always around four (Rayleigh scattering), independently of the shear rate, because the RBCs did not aggregate in the solution. Conversely, the spectral slope of the plasma sample was lower than four at low shear rates but approached four by increasing the shear rate, because the aggregations were presumably dissolved by the high shear rate. Moreover, the MBF of the plasma sample decreased from 36 to 49 dB in both flow phantoms with increasing shear rates, from approximately 10 to 100 s−1. The variation in the spectral slope and MBF in the saline sample was comparable to the results of in vivo cases in healthy human jugular veins when the tissue and blood flow signals could be separated. Full article
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11 pages, 2129 KiB  
Article
Evaluation of Hepatic Fibrosis Using Ultrasound Backscattered Radiofrequency Signals and One-Dimensional Convolutional Neural Networks
by Yong Huang, Yan Zeng, Guangyu Bin, Qiying Ding, Shuicai Wu, Dar-In Tai, Po-Hsiang Tsui and Zhuhuang Zhou
Diagnostics 2022, 12(11), 2833; https://doi.org/10.3390/diagnostics12112833 - 17 Nov 2022
Cited by 8 | Viewed by 2400
Abstract
The early detection of hepatic fibrosis is of critical importance. Ultrasound backscattered radiofrequency signals from the liver contain abundant information about its microstructure. We proposed a method for characterizing human hepatic fibrosis using one-dimensional convolutional neural networks (CNNs) based on ultrasound backscattered signals. [...] Read more.
The early detection of hepatic fibrosis is of critical importance. Ultrasound backscattered radiofrequency signals from the liver contain abundant information about its microstructure. We proposed a method for characterizing human hepatic fibrosis using one-dimensional convolutional neural networks (CNNs) based on ultrasound backscattered signals. The proposed CNN model was composed of four one-dimensional convolutional layers, four one-dimensional max-pooling layers, and four fully connected layers. Ultrasound radiofrequency signals collected from 230 participants (F0: 23; F1: 46; F2: 51; F3: 49; F4: 61) with a 3-MHz transducer were analyzed. Liver regions of interest (ROIs) that contained most of the liver ultrasound backscattered signals were manually delineated using B-mode images reconstructed from the backscattered signals. ROI signals were normalized and augmented by using a sliding window technique. After data augmentation, the radiofrequency signal segments were divided into training sets, validation sets and test sets at a ratio of 80%:10%:10%. In the test sets, the proposed algorithm produced an area under the receive operating characteristic curve of 0.933 (accuracy: 91.30%; sensitivity: 92.00%; specificity: 90.48%), 0.997 (accuracy: 94.29%; sensitivity: 94.74%; specificity: 93.75%), 0.818 (accuracy: 75.00%; sensitivity: 69.23%; specificity: 81.82%), and 0.934 (accuracy: 91.67%; sensitivity: 88.89%; specificity: 94.44%) for diagnosis liver fibrosis stage ≥F1, ≥F2, ≥F3, and ≥F4, respectively. Experimental results indicated that the proposed deep learning algorithm based on ultrasound backscattered signals yields a satisfying performance when diagnosing hepatic fibrosis stages. The proposed method may be used as a new quantitative ultrasound approach to characterizing hepatic fibrosis. Full article
(This article belongs to the Special Issue Ultrasound Imaging in Digestive and Kidney Diseases)
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10 pages, 2052 KiB  
Article
Transmastoid Ultrasound Detection of Middle Ear Effusion and Its Association with Clinical Audiometric Tests
by Chin-Kuo Chen, Yung-Liang Wan, Li-Chun Hsieh and Po-Hsiang Tsui
Life 2022, 12(4), 599; https://doi.org/10.3390/life12040599 - 18 Apr 2022
Cited by 2 | Viewed by 2324
Abstract
Medical history taking, otoscopy, tympanometry, and audiometry are clinical methods to diagnose middle ear effusion (MEE); however, these procedures are experience-dependent and result in misdiagnosis under unfavorable conditions of the external auditory canal in non-cooperative young children. This study aimed to explore the [...] Read more.
Medical history taking, otoscopy, tympanometry, and audiometry are clinical methods to diagnose middle ear effusion (MEE); however, these procedures are experience-dependent and result in misdiagnosis under unfavorable conditions of the external auditory canal in non-cooperative young children. This study aimed to explore the use of transmastoid ultrasound combined with the Nakagami parameter analysis to detect MEE in children aged 3–5 years and to compare the proposed method with clinical evaluation methods. A total of forty subjects were enrolled; for each subject, a single-element ultrasound transducer of 2.25 MHz was used to measure backscattered signals returned from the mastoid for estimating the Nakagami parameter, which is a measure of the echo amplitude distribution. Tympanogram and hearing loss were also measured for comparisons. The results showed that the Nakagami parameter in the patients with MEE was significantly larger than that of the normal group (p < 0.05). The area under the receiver operating characteristic curve (AUROC) for using the Nakagami parameter to detect MEE was 0.90, and the sensitivity, specificity, and accuracy were 82.5%, 97.5%, and 79.6%, respectively. The Nakagami parameter for tympanogram types B/C was higher than that for tympanogram type A (p < 0.05); it was also higher in the subjects with hearing loss (p < 0.05). Quantitative transmastoid ultrasound based on the Nakagami parameter analysis has the potential to detect MEE and evaluate hearing loss. Full article
(This article belongs to the Special Issue Ultrasound Imaging in Medicine Research)
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21 pages, 9770 KiB  
Article
Simulation of Ultrasound RF Signals Backscattered from a 3D Model of Pulsating Artery Surrounded by Tissue
by Monika Makūnaitė, Rytis Jurkonis, Arūnas Lukoševičius and Mindaugas Baranauskas
Diagnostics 2022, 12(2), 232; https://doi.org/10.3390/diagnostics12020232 - 18 Jan 2022
Cited by 1 | Viewed by 2554
Abstract
Arterial stiffness is an independent predictor of cardiovascular events. The motion of arterial tissues during the cardiac cycle is important as a mechanical deformation representing vessel elasticity and is related to arterial stiffness. In addition, arterial pulsation is the main source of endogenous [...] Read more.
Arterial stiffness is an independent predictor of cardiovascular events. The motion of arterial tissues during the cardiac cycle is important as a mechanical deformation representing vessel elasticity and is related to arterial stiffness. In addition, arterial pulsation is the main source of endogenous tissue micro-motions currently being studied for tissue elastography. Methods based on artery motion detection are not applied in clinical practice these days, because they must be carefully investigated in silico and in vitro before wide usage in vivo. The purpose of this paper is to propose a dynamic 3D artery model capable of reproducing the biomechanical behavior of human blood vessels surrounded by elastic tissue for endogenous deformation elastography developments and feasibility studies. The framework is based on a 3D model of a pulsating artery surrounded by tissue and simulation of linear scanning by Field II software to generate realistic dynamic RF signals and B-mode ultrasound image sequential data. The model is defined by a spatial distribution of motions, having patient-specific slopes of radial and longitudinal motion components of the artery wall and surrounding tissues. It allows for simulating the quantified mechanical micro-motions in the volume of the model. Acceptable simulation errors calculated between modeled motion patterns and those estimated from simulated RF signals and B-scan images show that this approach is suitable for the development and validation of elastography algorithms based on motion detection. Full article
(This article belongs to the Special Issue Advances in Carotid Artery Imaging)
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13 pages, 4325 KiB  
Article
Diagnosis of Bone Mineral Density Based on Backscattering Resonance Phenomenon Using Coregistered Functional Laser Photoacoustic and Ultrasonic Probes
by Lifeng Yang, Chulin Chen, Zhaojiang Zhang and Xin Wei
Sensors 2021, 21(24), 8243; https://doi.org/10.3390/s21248243 - 9 Dec 2021
Cited by 5 | Viewed by 3123
Abstract
Dual-energy X-ray absorptiometry (DXA) machines based on bone mineral density (BMD) represent the gold standard for osteoporosis diagnosis and assessment of fracture risk, but bone strength and toughness are strongly correlated with bone collagen content (CC). Early detection of osteoporosis combined with BMD [...] Read more.
Dual-energy X-ray absorptiometry (DXA) machines based on bone mineral density (BMD) represent the gold standard for osteoporosis diagnosis and assessment of fracture risk, but bone strength and toughness are strongly correlated with bone collagen content (CC). Early detection of osteoporosis combined with BMD and CC will provide improved predictability for avoiding fracture risk. The backscattering resonance (BR) phenomenon is present in both ultrasound (US) and photoacoustic (PA) signal transmissions through bone, and the peak frequencies of BR can be changed with BM and CC. This phenomenon can be explained by the formation of standing waves within the pores. Simulations were then conducted for the same bone µCT images and the resulting resonance frequencies were found to match those predicted using the standing wave hypothesis. Experiments were performed on the same bone sample using an 808 nm wavelength laser as the PA source and 3.5 MHz ultrasonic transducer as the US source. The backscattering resonance effect was observed in the transmitted waves. These results verify our hypothesis that the backscattering resonance phenomenon is present in both US and PA signal transmissions and can be explained using the standing waves model, which will provide a suitable method for the early detection of osteoporosis. Full article
(This article belongs to the Special Issue Micro-/Nano-Fiber Sensors and Optical Integration Devices)
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23 pages, 5591 KiB  
Article
Main Uncertainties in the RF Ultrasound Scanning Simulation of the Standard Ultrasound Phantoms
by Monika Makūnaitė, Rytis Jurkonis, Arūnas Lukoševičius and Mindaugas Baranauskas
Sensors 2021, 21(13), 4420; https://doi.org/10.3390/s21134420 - 28 Jun 2021
Cited by 3 | Viewed by 3761
Abstract
Ultrasound echoscopy technologies are continuously evolving towards new modalities including quantitative parameter imaging, elastography, 3D scanning, and others. The development and analysis of new methods and algorithms require an adequate digital simulation of radiofrequency (RF) signal transformations. The purpose of this paper is [...] Read more.
Ultrasound echoscopy technologies are continuously evolving towards new modalities including quantitative parameter imaging, elastography, 3D scanning, and others. The development and analysis of new methods and algorithms require an adequate digital simulation of radiofrequency (RF) signal transformations. The purpose of this paper is the quantitative evaluation of RF signal simulation uncertainties in resolution and contrast reproduction with the model of a phased array transducer. The method is based on three types of standard physical phantoms. Digital 3D models of those phantoms are composed of point scatterers representing the weak backscattering of the background material and stronger backscattering from inclusions. The simulation results of echoscopy with sector scanning transducer by Field II software are compared with the RF output of the Ultrasonix scanner after scanning standard phantoms with 2.5 MHz phased array. The quantitative comparison of axial, lateral, and elevation resolutions have shown uncertainties from 9 to 22% correspondingly. The echoscopy simulation with two densities of scatterers is compared with contrast phantom imaging on the backscattered RF signals and B-scan reconstructed image, showing that the main sources of uncertainties limiting the echoscopy RF signal simulation adequacy are an insufficient knowledge of the scanner and phantom’s parameters. The attempt made for the quantitative evaluation of simulation uncertainties shows both problems and the potential of echoscopy simulation in imaging technology developments. The analysis presented could be interesting for researchers developing quantitative ultrasound imaging and elastography technologies looking for simulated raw RF signals comparable to those obtained from real ultrasonic scanning. Full article
(This article belongs to the Special Issue Ultrasound Imaging and Sensing)
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