scholarly journals Speckle Track Analysis of Ultrasound Images Produce Reliable Measures of Supraspinatus Tendon Strain During a Maximal Isometric Contraction

2020 ◽  
pp. 1-7
Author(s):  
Mark Timmons ◽  
Gregory McClanahan ◽  
Mark Timmons
Keyword(s):  
Systematic Error ◽  
Speckle Tracking ◽  
Axial Strain ◽  
Ultrasound Image ◽  
Supraspinatus Tendon ◽  
Ultrasound Images ◽  
Good Reliability ◽  
Strain Measurements ◽  
Tendon Strain ◽  
Track Analysis

Introduction: Ultrasound speckle tracking is an emergent method in studying musculoskeletal physiology and disease. The precision and reliability of supraspinatus tendon strain measurements have not been explored. The purpose of this study was to examine the reliability of speckle tracking to measure supraspinatus tendon strain. Methods: Forty-two (42) participants participated in this study. Five (5) ultrasound images of the participant’s right shoulder supraspinatus tendon were collected during a maximal voluntary isometric abduction contraction. Cine loop video files of the 5 imaging trials were imported into Ncorr software for speckle track analysis. Axial and longitudinal strain measurements were made for the bursal side, midsubstance, and joint side of the thickest portion of the supraspinatus tendon. Reliability of the strain measures was determined using interclass correlation coefficients (ICC). Bland-Altman plots were created in order to explore systematic error. Results: Mean strain of the supraspinatus tendon ranged from 1.791 to -2.120 %. ICC values for the longitudinal and axial strains of both within and between images were high (>0.9) for all locations of the tendon, demonstrating very good reliability. The 95% for the MDC was large for all measurements of strain, except the axial strain at the mid-substance demonstrating poor precision. Conclusion: The results of the investigation show evidence of very good reliability, poor precision, and some evidence of systematic error. The very good ICC values support the hypothesis that speckle tracking does produce reliable strain measurements. The large MDC values do not support the hypothesis that speckle tracking produces precise strain measurements. Improvements in ultrasound image quality and the shoulder stabilization process need to be made before ultrasound speckle tracking will be a viable research method for the supraspinatus tendon.

Automatic Measurement of Pennation Angle from Ultrasound Images using Resnets

2021 ◽  
Vol 43 (2) ◽  
pp. 74-87
Author(s):  
Weimin Zheng ◽  
Shangkun Liu ◽  
Qing-Wei Chai ◽  
Jeng-Shyang Pan ◽  
Shu-Chuan Chu
Keyword(s):  
Muscle Fibers ◽  
Ultrasound Image ◽  
Automatic Measurement ◽  
Pennation Angle ◽  
Reference Line ◽  
Ultrasound Images ◽  
Single Image ◽  
Angle Measuring ◽  
Sequential Image ◽  
Robust Measurements

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.

scholarly journals Curvelet based automatic segmentation of supraspinatus tendon from ultrasound image: a focused assistive diagnostic method

2014 ◽  
Vol 13 (1) ◽  
pp. 157 ◽  
Author(s):  
Rishu Gupta ◽  
Irraivan Elamvazuthi ◽  
Sarat Dass ◽  
Ibrahima Faye ◽  
Pandian Vasant ◽  
...  
Keyword(s):  
Diagnostic Method ◽  
Automatic Segmentation ◽  
Ultrasound Image ◽  
Supraspinatus Tendon

3D Tendon Strain Estimation Using High-frequency Volumetric Ultrasound Images: A Feasibility Study

2017 ◽  
Vol 40 (2) ◽  
pp. 67-83 ◽  
Author(s):  
Catarina Carvalho ◽  
Pieter Slagmolen ◽  
Stijn Bogaerts ◽  
Lennart Scheys ◽  
Jan D’hooge ◽  
...  
Keyword(s):  
Feasibility Study ◽  
High Frequency ◽  
Ultrasound Images ◽  
Strain Estimation ◽  
Tendon Strain ◽  
Volumetric Ultrasound

scholarly journals Performance Evaluation of Contour Based Segmentation Methods for Ultrasound Images

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
R. J. Hemalatha ◽  
V. Vijaybaskar ◽  
T. R. Thamizhvani
Keyword(s):  
Active Contour ◽  
Performance Metrics ◽  
Ultrasound Image ◽  
Medical Image Segmentation ◽  
Similarity Criteria ◽  
Support Vector ◽  
Svm Classifier ◽  
Ultrasound Images ◽  
Segmentation Method ◽  
Region Detection

Active contour methods are widely used for medical image segmentation. Using level set algorithms the applications of active contour methods have become flexible and convenient. This paper describes the evaluation of the performance of the active contour models using performance metrics and statistical analysis. We have implemented five different methods for segmenting the synovial region in arthritis affected ultrasound image. A comparative analysis between the methods of segmentation was performed and the best segmentation method was identified using similarity criteria, standard error, and F-test. For further analysis, classification of the segmentation techniques using support vector machine (SVM) classifier is performed to determine the absolute method for synovial region detection. With these results, localized region based active contour named Lankton method is defined to be the best segmentation method.

scholarly journals Ultrasonography in physiotherapy and rehabilitation

2021 ◽  
pp. 1-3
Author(s):  
Barassi Giovanni ◽  
Guerri Sergio ◽  
Tavani Roberta ◽  
Ricucci Giampiero ◽  
De Luca Giorgia ◽  
...  
Keyword(s):  
Ultrasound Image ◽  
Muscle Stiffness ◽  
Ultrasound Images ◽  
Tendon Tissue ◽  
Invasive Approach ◽  
Know How ◽  
Non Invasive ◽  
Load Transmission ◽  
Intensity Information

There is an interrelation with ultrasound / physiotherapist and the duty of the physiotherapist to know how to perform ultrasound examinations alone, not for diagnostic purposes, to follow the evolution of the therapeutic cycle of physiotherapy. For this reason, ultrasound image analysis (US) is a promising non-invasive approach that uses load-dependent changes in the intensity of the echo to characterize the rigidity of muscle and tendon tissue. The purpose of this contribution is to improve the use of ultrasound images (US) and the role of the physiotherapist, who are able to detect localized changes, in particular in stiffness of the tendon due to partial and full-thickness tendon tears. Image intensity information is less sensitive for identifying load transmission variations resulting from partial thickness cuts initiated on the joint side. Ultrasound images can be useful for quantitatively assessing the variations dependent on the tendon load and muscle stiffness in physiotherapy and that the interruption of the behavior of the acousto-elastic ultrasound images can be indicative of substantial damage to the muscle or tendon.

scholarly journals Texture Based Quality Analysis of Simulated Synthetic Ultrasound Images Using Local Binary Patterns

2017 ◽  
Author(s):  
Prerna Singh ◽  
Ramakrishnan Mukundan ◽  
Rex De Ryke
Keyword(s):  
Quality Assessment ◽  
Image Quality Assessment ◽  
Ultrasound Image ◽  
Texture Feature ◽  
Ground Truth ◽  
Speckle Noise ◽  
Local Binary Patterns ◽  
Quality Analysis ◽  
Ultrasound Images ◽  
Ground Truth Data

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modelling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

scholarly journals Enhancing ultrasound texture differences for developing an in vivo 'virtual histology' approach to bovine ovarian imaging

2007 ◽  
Vol 19 (8) ◽  
pp. 910 ◽  
Author(s):  
Mark G. Eramian ◽  
Gregg P. Adams ◽  
Roger A. Pierson
Keyword(s):  
Image Processing ◽  
Ultrasound Image ◽  
Ultrasound Images ◽  
Virtual Histology ◽  
Form And Function ◽  
Non Invasive ◽  
Candidate Image ◽  
And Function ◽  
Processing Techniques

A ‘virtual histology’ can be thought of as the ‘staining’ of a digital ultrasound image via image processing techniques in order to enhance the visualisation of differences in the echotexture of different types of tissues. Several candidate image-processing algorithms for virtual histology using ultrasound images of the bovine ovary were studied. The candidate algorithms were evaluated qualitatively for the ability to enhance the visual differences in intra-ovarian structures and quantitatively, using standard texture description features, for the ability to increase statistical differences in the echotexture of different ovarian tissues. Certain algorithms were found to create textures that were representative of ovarian micro-anatomical structures that one would observe in actual histology. Quantitative analysis using standard texture description features showed that our algorithms increased the statistical differences in the echotexture of stroma regions and corpus luteum regions. This work represents a first step toward both a general algorithm for the virtual histology of ultrasound images and understanding dynamic changes in form and function of the ovary at the microscopic level in a safe, repeatable and non-invasive way.

Denoising Ultrasound Medical Images

2017 ◽  
pp. 761-775
Author(s):  
A.S.C.S. Sastry ◽  
P.V.V. Kishore ◽  
Ch. Raghava Prasad ◽  
M.V.D. Prasad
Keyword(s):  
Image Quality ◽  
Medical Images ◽  
Ultrasound Image ◽  
Similarity Index ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Soft Thresholding ◽  
Block Based

Medical ultrasound imaging has revolutioned the diagnostics of human body in the last few decades. The major drawback of ultrasound medical images is speckle noise. Speckle noise in ultrasound images is because of multiple reflections of ultrasound waves from hard tissues. Speckle noise degrades the medical ultrasound images lessening the visible quality of the image. The aim of this paper is to improve the image quality of ultrasound medical images by applying block based hard and soft thresholding on wavelet coefficients. Medical ultrasound image transformation to wavelet domain uses debauchee's mother wavelet. Divide the approximate and detailed coefficients into uniform blocks of size 8×8, 16×16, 32×32 and 64×64. Hard and soft thresholding on these blocks of approximate and detailed coefficients reduces speckle noise. Inverse transformation to original spatial domain produces a noise reduced ultrasound image. Experiments on medical ultrasound images obtained from diagnostic centers in Vijayawada, India show good improvements to ultrasound images visually. Quality of improved images in measured using peak signal to noise ratio (PSNR), image quality index (IQI), structural similarity index (SSIM).

Development of Ultrasound Imaging CAD Tool for Assessment of Pathologies in Supraspinatus Tendon

2017 ◽  
pp. 614-654
Author(s):  
Rishu Gupta ◽  
Irraivan Elamvazuthi ◽  
John George
Keyword(s):  
Supraspinatus Tendon ◽  
Ultrasound Images ◽  
Medical Work ◽  
Non Invasive ◽  
Computer Aided ◽  
Cad Tool ◽  
Intuitive User Interface ◽  
Aided Diagnosis ◽  
Shape And Size

Non-invasive diagnostic imaging methods for diagnosis of pathological conditions is increasingly gaining popularity resulting from speedy and effective recovery during follow up in several clinical trials. The accuracy of the diagnosis depends on the experience and knowledge of physicians conducting the trial. In such scenario, the need for quantitative measures for details such as shape and size of tissue can assist physicians for better intuitive understanding of tissue and its pathologies. Computer aided diagnosis (CAD) tool incorporating methods for segmentation, texture analysis and area computation can increase the accuracy of diagnosis by providing quantitative analysis of the image. This chapter briefly describes issues and challenges for building the CAD tool followed by brief description about the methods involved. The methods are validation are also discussed briefly. To summarize the work, brief discussion about a new software or CAD tool for diagnosis of pathologies supraspinatus tendon with the help of ultrasound images is provided. The new software has an intuitive user interface which is easy, quick and suitable for medical work.

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