Ultrasonic Imaging最新文献_第10页

Spatial-frequency Analysis of the Anatomical Differences in Hamstring Muscles. 腘绳肌解剖差异的空间-频率分析。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2021-03-01 DOI: 10.1177/0161734621990707

Scott K Crawford, Kenneth S Lee, Greg R Bashford, Bryan C Heiderscheit

{"title":"Spatial-frequency Analysis of the Anatomical Differences in Hamstring Muscles.","authors":"Scott K Crawford, Kenneth S Lee, Greg R Bashford, Bryan C Heiderscheit","doi":"10.1177/0161734621990707","DOIUrl":"https://doi.org/10.1177/0161734621990707","url":null,"abstract":"Spatial frequency analysis (SFA) is a quantitative ultrasound method that characterizes tissue organization. SFA has been used for research involving tendon injury, but may prove useful in similar research involving skeletal muscle. As a first step, we investigated if SFA could detect known architectural differences within hamstring muscles. Ultrasound B-mode images were collected bilaterally at locations corresponding to proximal, mid-belly, and distal thirds along the hamstrings from 10 healthy participants. Images were analyzed in the spatial frequency domain by applying a two-dimensional Fourier Transform in all 6.5 × 6.5 mm kernels in a region of interest corresponding to the central portion of the muscle. SFA parameters (peak spatial frequency radius [PSFR], maximum frequency amplitude [Mmax], sum of frequencies [Sum], and ratio of Mmax to Sum [Mmax%]) were extracted from each muscle location and analyzed by separate linear mixed effects models. Significant differences were observed proximo-distally in PSFR (p = .039), Mmax (p < .0001), and Sum (p < .0001), consistent with architectural descriptions of the hamstring muscles. These results suggest that SFA can detect regional differences of healthy tissue structure within the hamstrings-an important finding for future research in regional muscle structure and mechanics.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734621990707","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25350869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Automatic Lumen Border Detection in IVUS Images Using Deep Learning Model and Handcrafted Features. 基于深度学习模型和手工特征的IVUS图像的自动流明边界检测。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2021-03-01 Epub Date: 2021-01-15 DOI: 10.1177/0161734620987288

Kai Li, Jijun Tong, Xinjian Zhu, Shudong Xia

{"title":"Automatic Lumen Border Detection in IVUS Images Using Deep Learning Model and Handcrafted Features.","authors":"Kai Li, Jijun Tong, Xinjian Zhu, Shudong Xia","doi":"10.1177/0161734620987288","DOIUrl":"https://doi.org/10.1177/0161734620987288","url":null,"abstract":"In the clinical analysis of Intravascular ultrasound (IVUS) images, the lumen size is an important indicator of coronary atherosclerosis, and is also the premise of coronary artery disease diagnosis and interventional treatment. In this study, a fully automatic method based on deep learning model and handcrafted features is presented for the detection of the lumen borders in IVUS images. First, 193 handcrafted features are extracted from the IVUS images. Then hybrid feature vectors are constructed by combining handcrafted features with 64 high-level features extracted from U-Net. In order to obtain the feature subsets with larger contribution, we employ the extended binary cuckoo search for feature selection. Finally, the selected 36-dimensional hybrid feature subset is used to classify the test images using dictionary learning based on kernel sparse coding. The proposed algorithm is tested on the publicly available dataset and evaluated using three indicators. Through ablation experiments, mean value of the experimental results (Jaccard: 0.88, Hausdorff distance: 0.36, Percentage of the area difference: 0.06) prove to be effective improving lumen border detection. Furthermore, compared with the recent methods used on the same dataset, the proposed method shows good performance and high accuracy.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620987288","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38821597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Automatic Measurement of Pennation Angle from Ultrasound Images using Resnets. 用Resnets自动测量超声图像笔触角。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2021-03-01 DOI: 10.1177/0161734621989598

Weimin Zheng, Shangkun Liu, Qing-Wei Chai, Jeng-Shyang Pan, Shu-Chuan Chu

{"title":"Automatic Measurement of Pennation Angle from Ultrasound Images using Resnets.","authors":"Weimin Zheng, Shangkun Liu, Qing-Wei Chai, Jeng-Shyang Pan, Shu-Chuan Chu","doi":"10.1177/0161734621989598","DOIUrl":"https://doi.org/10.1177/0161734621989598","url":null,"abstract":"In this study, an automatic pennation angle measuring approach based on deep learning is proposed. Firstly, the Local Radon Transform (LRT) is used to detect the superficial and deep aponeuroses on the ultrasound image. Secondly, a reference line are introduced between the deep and superficial aponeuroses to assist the detection of the orientation of muscle fibers. The Deep Residual Networks (Resnets) are used to judge the relative orientation of the reference line and muscle fibers. Then, reference line is revised until the line is parallel to the orientation of the muscle fibers. Finally, the pennation angle is obtained according to the direction of the detected aponeuroses and the muscle fibers. The angle detected by our proposed method differs by about 1° from the angle manually labeled. With a CPU, the average inference time for a single image of the muscle fibers with the proposed method is around 1.6 s, compared to 0.47 s for one of the image of a sequential image sequence. Experimental results show that the proposed method can achieve accurate and robust measurements of pennation angle.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734621989598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25350868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

A Low-complexity Minimum-variance Beamformer Based on Orthogonal Decomposition of the Compounded Subspace. 基于复合子空间正交分解的低复杂度最小方差波束形成器。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2021-01-01 DOI: 10.1177/0161734620973945

Yinmeng Wang, Yanxing Qi, Yuanyuan Wang

{"title":"A Low-complexity Minimum-variance Beamformer Based on Orthogonal Decomposition of the Compounded Subspace.","authors":"Yinmeng Wang, Yanxing Qi, Yuanyuan Wang","doi":"10.1177/0161734620973945","DOIUrl":"https://doi.org/10.1177/0161734620973945","url":null,"abstract":"Minimum-variance (MV) beamforming, as a typical adaptive beamforming method, has been widely studied in medical ultrasound imaging. This method achieves higher spatial resolution than traditional delay-and-sum (DAS) beamforming by minimizing the total output power while maintaining the desired signals. However, it suffers from high computational complexity due to the heavy calculation load when determining the inverse of the high-dimensional matrix. Low-complexity MV algorithms have been studied recently. In this study, we propose a novel MV beamformer based on orthogonal decomposition of the compounded subspace (CS) of the covariance matrix in synthetic aperture (SA) imaging, which aims to reduce the dimensions of the covariance matrix and therefore reduce the computational complexity. Multiwave spatial smoothing is applied to the echo signals for the accurate estimation of the covariance matrix, and adaptive weight vectors are calculated from the low-dimensional subspace of the original covariance matrix. We conducted simulation, experimental and in vivo studies to verify the performance of the proposed method. The results indicate that the proposed method performs well in maintaining the advantage of high spatial resolution and effectively reduces the computational complexity compared with the standard MV beamformer. In addition, the proposed method shows good robustness against sound velocity errors.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620973945","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38744829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Computation of Photoacoustic Absorber Size from Deconvolved Photoacoustic Signal Using Estimated System Impulse Response. 利用估计系统脉冲响应计算反卷积光声信号的光声吸收体尺寸。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2021-01-01 DOI: 10.1177/0161734620977838

Nikita Rathi, Saugata Sinha, Bhargava Chinni, Vikram Dogra, Navalgund Rao

{"title":"Computation of Photoacoustic Absorber Size from Deconvolved Photoacoustic Signal Using Estimated System Impulse Response.","authors":"Nikita Rathi, Saugata Sinha, Bhargava Chinni, Vikram Dogra, Navalgund Rao","doi":"10.1177/0161734620977838","DOIUrl":"https://doi.org/10.1177/0161734620977838","url":null,"abstract":"Photoacoustic signal recorded by photoacoustic imaging system can be modeled as convolution of initial photoacoustic response by the photoacoustic absorber with the system impulse response. Our goal was to compute the size of photoacoustic absorber using the initial photoacoustic response, deconvolved from the recorded photoacoustic data. For deconvolution, we proposed to use the impulse response of the photoacoustic system, estimated using discrete wavelet transform based homomorphic filtering. The proposed method was implemented on experimentally acquired photoacoustic data generated by different phantoms and also verified by a simulation study involving photoacoustic targets, identical to the phantoms in experimental study. The photoacoustic system impulse response, which was estimated using the acquired photoacoustic signal corresponding to a lead pencil, was used to extract initial photoacoustic response corresponding to a mustard seed of 0.65 mm radius. The recovered radius values of the mustard seed, corresponding to the experimental and simulation studies were 0.6 mm and 0.7 mm.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620977838","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38744827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Nipple Localization in Automated Whole Breast Ultrasound Coronal Scans Using Ensemble Learning. 全乳超声冠状扫描中乳头定位的集成学习方法。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2021-01-01 DOI: 10.1177/0161734620974273

Alex Noel Joseph Raj, Ruban Nersisson, Vijayalakshmi G V Mahesh, Zhemin Zhuang

{"title":"Nipple Localization in Automated Whole Breast Ultrasound Coronal Scans Using Ensemble Learning.","authors":"Alex Noel Joseph Raj, Ruban Nersisson, Vijayalakshmi G V Mahesh, Zhemin Zhuang","doi":"10.1177/0161734620974273","DOIUrl":"https://doi.org/10.1177/0161734620974273","url":null,"abstract":"Nipple is a vital landmark in the breast lesion diagnosis. Although there are advanced computer-aided detection (CADe) systems for nipple detection in breast mediolateral oblique (MLO) views of mammogram images, few academic works address the coronal views of breast ultrasound (BUS) images. This paper addresses a novel CADe system to locate the Nipple Shadow Area (NSA) in ultrasound images. Here the Hu Moments and Gray-level Co-occurrence Matrix (GLCM) were calculated through an iterative sliding window for the extraction of shape and texture features. These features are then concatenated and fed into an Artificial Neural Network (ANN) to obtain probable NSA's. Later, contour features, such as shape complexity through fractal dimension, edge distance from the periphery and contour area, were computed and passed into a Support Vector Machine (SVM) to identify the accurate NSA in each case. The coronal plane BUS dataset is built upon our own, which consists of 64 images from 13 patients. The test results show that the proposed CADe system achieves 91.99% accuracy, 97.55% specificity, 82.46% sensitivity and 88% F-score on our dataset.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620974273","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38744828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated Pleural Line Detection Based on Radon Transform Using Ultrasound. 基于氡变换的超声胸膜线自动检测。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2021-01-01 DOI: 10.1177/0161734620976408

Jiangang Chen, Jiawei Li, Chao He, Wenfang Li, Qingli Li

{"title":"Automated Pleural Line Detection Based on Radon Transform Using Ultrasound.","authors":"Jiangang Chen, Jiawei Li, Chao He, Wenfang Li, Qingli Li","doi":"10.1177/0161734620976408","DOIUrl":"https://doi.org/10.1177/0161734620976408","url":null,"abstract":"It is of vital importance to identify the pleural line when performing lung ultrasound, as the pleural line not only indicates the interface between the chest wall and lung, but offers additional diagnostic information. In the current clinical practice, the pleural line is visually detected and evaluated by clinicians, which requires experiences and skills with challenges for the novice. In this study, we developed a computer-aided technique for automated pleural line detection using ultrasound. The method first utilized the Radon transform to detect line objects in the ultrasound images. The relation of the body mass index and chest wall thickness was then applied to estimate the range of the pleural thickness, based on which the pleural line was detected together with the consideration of the ultrasonic properties of the pleural line. The proposed method was validated by testing 83 ultrasound data sets collected from 21 pneumothorax patients. The pleural lines were successfully identified in 76 data sets by the automated method (successful detection rate 91.6%). In those successful cases, the depths of the pleural lines measured by the automated method agreed with those manually measured as confirmed with the Bland-Altman test. The measurement errors were below 5% in terms of the pleural line depth. As a conclusion, the proposed method could detect the pleural line in an automated manner in the defined data set. In addition, the method may potentially act as an alternative to visual inspection after further tests on more diverse data sets are performed in future studies.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620976408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38744826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Application of Contrast-Enhanced Ultrasound in the Differential Diagnosis of Different Molecular Subtypes of Breast Cancer. 超声造影在不同分子亚型乳腺癌鉴别诊断中的应用。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2020-11-01 DOI: 10.1177/0161734620959780

Xingyu Liang, Ziyao Li, Lei Zhang, Dongmo Wang, Jiawei Tian

{"title":"Application of Contrast-Enhanced Ultrasound in the Differential Diagnosis of Different Molecular Subtypes of Breast Cancer.","authors":"Xingyu Liang, Ziyao Li, Lei Zhang, Dongmo Wang, Jiawei Tian","doi":"10.1177/0161734620959780","DOIUrl":"https://doi.org/10.1177/0161734620959780","url":null,"abstract":"To explore the value of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of molecular subtypes of breast cancer. Sixty-two cases of breast cancer were divided into luminal epithelium A or B subtype (luminal A/B), Her-2 over-expression subtype and triple negative subtype (TN). CEUS and routine ultrasonography were performed for all patients before surgery. (1) The luminal epithelium subtype contrast enhancement pattern was more likely to present with radial edge (76.92%, p < 0.05) and low perfusion (69.23%, p < 0.05). The maximum intensity (IMAX) was lower in the luminal epithelium subtype (p < 0.05). (2) The Her-2 over-expression subtype contrast enhancement pattern was more likely to present with centripetal enhancement (93.75%, p < 0.05) and perfusion defect (75.0%, p < 0.05), and the time to peak (TTP) was shorter (80.0%, p < 0.05). (3) The contrast enhancement pattern of the triple negative subtype was shown to have a clear boundary. Compared to the other two subtypes, the triple negative subtype did not have significantly different perfusion parameters (p > 0.05). (4) Our study showed that the areas under the ROC curve for radial edge, low perfusion and IMAX for the luminal epithelium subtype breast lesions were 76.5%, 75.6%, and 82.1%, respectively. Additionally, the areas under the ROC curve for centripetal enhancement, perfusion defect and TTP for the Her-2 over-expression subtype breast lesions were 68.6%, 92.4%, and 97.8%, respectively. The sensitivity, specificity, and diagnostic accuracy of clear boundaries in detecting triple negative subtype breast lesions were 90.5%, 80.0%, and 91.9%, respectively.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620959780","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38461718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Fully Automatic Measurement of Intima-Media Thickness in Ultrasound Images of the Common Carotid Artery Based on Improved Otsu's Method and Adaptive Wind Driven Optimization. 基于改进Otsu方法和自适应风驱动优化的颈总动脉超声图像内膜-中膜厚度全自动测量

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2020-11-01 Epub Date: 2020-09-18 DOI: 10.1177/0161734620956897

Kun Wang, Yuanyuan Pu, Yufeng Zhang, Pei Wang

{"title":"Fully Automatic Measurement of Intima-Media Thickness in Ultrasound Images of the Common Carotid Artery Based on Improved Otsu's Method and Adaptive Wind Driven Optimization.","authors":"Kun Wang, Yuanyuan Pu, Yufeng Zhang, Pei Wang","doi":"10.1177/0161734620956897","DOIUrl":"https://doi.org/10.1177/0161734620956897","url":null,"abstract":"The intima media thickness (IMT) of the common carotid artery (CCA) can be used to predict the risk of atherosclerosis. Many image segmentation techniques have been used for IMT measurement. However, severe noise in the ultrasound image can lead to erroneous segmentation results. To improve the robustness to noise, a fully automatic method, based on an improved Otsu's method and an adaptive wind-driven optimization technique, is proposed for estimating the IMT (denoted as \"improved Otsu-AWDO\"). First, an advanced despeckling filter, i.e., \" Nagare's filter\" is used to address the speckle noise in the carotid ultrasound images. Next, an improved fuzzy contrast method (IFC) is used to enhance the region of the intima media complex (IMC) in the blurred filtered images. Then, a new method is used for automatic extraction of the region of interest (ROI). Finally, the lumen intima interface and media adventitia interface are segmented from the IMC using improved Otsu-AWDO. Then, 156 B-mode longitudinal carotid ultrasound images of six different datasets are used to evaluate the performance of the automatic measurements. The results indicate that the absolute error of proposed method is only 10.1 ± 9.6 (mean ± std in μm). Moreover, the proposed method has a correlation coefficient as high as 0.9922, and a bias as low as 0.0007. From comparison with previous methods, we can conclude that the proposed method has strong robustness and can provide accurate IMT estimations.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620956897","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38396280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Skeletal Muscle Fatigue State Evaluation with Ultrasound Image Entropy. 基于超声图像熵的骨骼肌疲劳状态评价。

IF 2.3 4区医学

Ultrasonic Imaging Pub Date : 2020-11-01 Epub Date: 2020-08-28 DOI: 10.1177/0161734620952683

Pan Li, Xuebing Yang, Guanjun Yin, Jianzhong Guo

{"title":"Skeletal Muscle Fatigue State Evaluation with Ultrasound Image Entropy.","authors":"Pan Li, Xuebing Yang, Guanjun Yin, Jianzhong Guo","doi":"10.1177/0161734620952683","DOIUrl":"https://doi.org/10.1177/0161734620952683","url":null,"abstract":"Muscle fatigue often occurs over a long period of exercise, and it can increase the risk of muscle injury. Evaluating the state of muscle fatigue can avoid unnecessary overtraining and injury of the muscle. Ultrasound imaging can non-invasively visualize muscle tissue in real-time. Image entropy is commonly used to characterize the texture of an image. In this study, we evaluated changes in the ultrasound image entropy (USIE) during the fatigue process. Twelve volunteers performed static sustained contractions of biceps brachii at four different intensities (20%, 30%, 40%, and 50% of maximal voluntary contraction torque). The ultrasound images and surface electromyography (sEMG) signals were acquired during exercise to fatigue. We found that (1) the root-mean-square of the sEMG signal increased, the USIE decreased significantly with time during the sustained contractions; (2) the maximum endurance time (MET) and the decline percentage of USIE were significantly different (p < .05) among the four contraction intensities; (3) the decline slope of USIE of the same volunteer was basically the same at different contraction intensities. The USIE could be a new method for the evaluation of skeletal muscle fatigue state.","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0161734620952683","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38320658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8