scholarly journals Compressed Sensing Image Reconstruction of Ultrasound Image for Treatment of Early Traumatic Myositis Ossificans of Elbow Joint by Electroacupuncture

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yi Zhu ◽  
Mengyuan Sheng ◽  
Yuanming Ouyang ◽  
Lichang Zhong ◽  
Kun Liu ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Heterotopic Ossification ◽  
Ultrasound Imaging ◽  
External Fixator ◽  
Elbow Joint ◽  
Acoustic Scattering ◽  
Ultrasound Image ◽  
Ultrasound Images ◽  
Image Library

This article conducts a retrospective analysis of 500 patients with posttraumatic elbow dysfunction admitted to our department from March 2019 to September 2020. The average time from injury to operation is 11 months (2–20 months). We adopt a personalized treatment method to completely remove the hyperplastic adhesion tissue and heterotopic ossification around the joint, remove part of the joint capsule and ligament, and release it to achieve maximum function. After the operation, an external fixator was used to stabilize the loosened elbow joint, and the patient was guided to perform rehabilitation exercises with the aid of a hinged external fixator, and celecoxib was used to prevent heterotopic ossification. Mayo functional scoring system was used to evaluate the curative effect before and after surgery. The rapid realization of ultrasound imaging under the framework of compressed sensing is studied. Under the premise of ensuring the quality of ultrasound imaging reconstruction, the theory of ultrasound imaging is improved, and a plane wave acoustic scattering ultrasound echo model is established. On this basis, the theory of compressed sensing is introduced, the mathematical model of compressed sensing reconstruction is established, and the fast iterative shrinkage thresholding algorithm (FISTA) of compressed sensing reconstruction is improved to reduce the computational complexity and the number of iterations. This article uses FISTA directly to reconstruct medical ultrasound images, and the reconstruction results are not ideal. Therefore, a simulation model of FISTA training and testing was established using the standard image library. By adding different intensities of noise to all images in the image library, the influence of noise intensity on the quality of FISTA reconstructed images is analyzed, and it is found that the FISTA model has requirements for the quality of the images to be reconstructed and the training set images. In this paper, Rob’s blind deconvolution restoration algorithm is used to preprocess the original ultrasound image. The clarity of the texture details of the restored ultrasound image is significantly improved, and the image quality is improved, which meets the above requirements. This paper finally formed a reconstruction model suitable for ultrasound images. The reconstruction strategy verified by the ultrasound images provided by the Institute of Ultrasound Imaging of a medical university has achieved a significant improvement in the quality of ultrasound images.

scholarly journals Empirical Analysis of Deep Convolutional Generative Adversarial Network for Ultrasound Image Synthesis

2021 ◽  
Vol 15 (1) ◽  
pp. 71-77
Author(s):  
Dheeraj Kumar ◽  
Mayuri A. Mehta ◽  
Indranath Chatterjee
Keyword(s):  
Empirical Analysis ◽  
Ultrasound Imaging ◽  
Ultrasound Image ◽  
Generative Adversarial Networks ◽  
Ultrasound Images ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Adversarial Networks ◽  
Synthetic Images

Introduction: Recent research on Generative Adversarial Networks (GANs) in the biomedical field has proven the effectiveness in generating synthetic images of different modalities. Ultrasound imaging is one of the primary imaging modalities for diagnosis in the medical domain. In this paper, we present an empirical analysis of the state-of-the-art Deep Convolutional Generative Adversarial Network (DCGAN) for generating synthetic ultrasound images. Aims: This work aims to explore the utilization of deep convolutional generative adversarial networks for the synthesis of ultrasound images and to leverage its capabilities. Background: Ultrasound imaging plays a vital role in healthcare for timely diagnosis and treatment. Increasing interest in automated medical image analysis for precise diagnosis has expanded the demand for a large number of ultrasound images. Generative adversarial networks have been proven beneficial for increasing the size of data by generating synthetic images. Objective: Our main purpose in generating synthetic ultrasound images is to produce a sufficient amount of ultrasound images with varying representations of a disease. Methods: DCGAN has been used to generate synthetic ultrasound images. It is trained on two ultrasound image datasets, namely, the common carotid artery dataset and nerve dataset, which are publicly available on Signal Processing Lab and Kaggle, respectively. Results: Results show that good quality synthetic ultrasound images are generated within 100 epochs of training of DCGAN. The quality of synthetic ultrasound images is evaluated using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM). We have also presented some visual representations of the slices of generated images for qualitative comparison. Conclusion: Our empirical analysis reveals that synthetic ultrasound image generation using DCGAN is an efficient approach. Other: In future work, we plan to compare the quality of images generated through other adversarial methods such as conditional GAN, progressive GAN.

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).

scholarly journals An Ultrasound Imaging-Guided Robotic HIFU Ablation Experimental System and Accuracy Evaluations

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Chih Yu An ◽  
Jia Hao Syu ◽  
Ching Shiow Tseng ◽  
Chih-Ju Chang
Keyword(s):  
Standard Deviation ◽  
Ultrasound Imaging ◽  
Focused Ultrasound ◽  
Ultrasound Image ◽  
Experimental System ◽  
High Intensity Focused Ultrasound ◽  
Ultrasound Images ◽  
Tumor Treatment ◽  
Positioning Control ◽  
Hifu Ablation

In recent years, noninvasive thermal treatment by using high-intensity focused ultrasound (HIFU) has high potential in tumor treatment. The goal of this research is to develop an ultrasound imaging-guided robotic HIFU ablation system for tumor treatment. The system integrates the technologies of ultrasound image-assisted guidance, robotic positioning control, and HIFU treatment planning. With the assistance of ultrasound image guidance technology, the tumor size and location can be determined from ultrasound images as well as the robotic arm can be controlled to position the HIFU transducer to focus on the target tumor. After the development of the system, several experiments were conducted to measure the positioning accuracy of this system. The results show that the average positioning error is 1.01 mm with a standard deviation 0.34, and HIFU ablation accuracy is 1.32 mm with a standard deviation 0.58, which means this system is confirmed with its possibility and accuracy.

scholarly journals Early detection of joint abnormalities from ultrasound images

2018 ◽  
Vol 7 (2.25) ◽  
pp. 105
Author(s):  
R J. Hemalatha ◽  
Dr V. Vijaybaskar ◽  
A Josephin Arockia Dhivya ◽  
. .
Keyword(s):  
Early Detection ◽  
Ultrasound Image ◽  
Computer Software ◽  
Pso Algorithm ◽  
Optimization Techniques ◽  
Optimization Approach ◽  
Ultrasound Images ◽  
Processing Techniques ◽  
Modern Image

Musculoskeletal ultrasound is effective for the early detection of joint abnormalities like erosion, effusion, synovitis and inflammation. Computer software is developed for segmentation of joint ultrasound image to diagnose the defect. The objective of developing this paper is to achieve early diagnosis of joint disorders by segmentation of ultrasound image with different algorithms. Ultrasound machine with high resolution probe can be used for development & findings of joints by the orthopaedician, rheumatologist and sports physician. These find-ings are done by processing the ultrasound images of patient joint using modern image processing techniques. Therefore algorithms has been designed and developed for analysis of medical images that is musculo ultrasound image based on optimization approach, using genet-ic algorithm and PSO algorithm. To improve the better quality of the image many improvisation techniques have been introduced. Hence, these algorithms perform better segmentation and identification of joint abnormalities. The analysis of ultrasound image is directly based on image segmentation steps, pre-processing, filtering, feature extraction and analysis of these extracted features by finding the output using different optimization techniques. In proposed method, efforts have been made to exhibit the procedure for finding and segmenting the mus-culoskeletal images of abnormal joints. The present approaches are segmentation operation on ultrasound images by applying genetic and PSO algorithm. The comparison between these algorithms is done, such that the algorithm itself analyses the whole image and perform the segmentation and detection of abnormalities perfectly   

QUANTITATIVE ASSESSMENT OF GINGIVAL INFLAMMATION USING HIGH-RESOLUTION ULTRASOUNDEX-VIVO

2018 ◽  
Vol 18 (03) ◽  
pp. 1850012 ◽  
Author(s):  
AHMED M. SAYED ◽  
RACHEL LAMARCK ◽  
ELISA CRUZ ◽  
EROS CHAVES ◽  
OSAMA M. MUKDADI
Keyword(s):  
High Resolution ◽  
Ultrasound Imaging ◽  
Ex Vivo ◽  
Ultrasound Image ◽  
Strong Relationship ◽  
Ultrasound Images ◽  
Gingival Inflammation ◽  
Cross Sectional ◽  
Diagnostic Potential ◽  
Image Pairs

This study investigates the feasibility of using high-resolution ultrasound imaging echogenicity to quantitatively diagnose gingival inflammation. Gingival samples were extracted from the study participants during gingivectomy procedures. Ultrasound mechanical scanning of the samples was immediately conducted ex-vivo to render cross-sectional images of high resolution, at different locations. Samples’ histological preparation and analysis was followed after performing ultrasound imaging. Histological sections were then matched with ultrasound images at different sections for each gingival sample. The matched image pairs were used to estimate two quantitative measures; relative inflammation area and ultrasound image echogenicity. These parameters were employed to judge the diagnostic potential of gingival ultrasound imaging. The results show that ultrasound images exhibited low intensity levels at the inflamed gingival regions, while healthy layers showed higher intensity levels. The relative area parameter implied a strong relationship between ultrasound and histological images. Ultrasound echogenicity was found to be statistically significant in differentiating between some inflammation degrees in the studied gingival samples. In summary, ultrasound imaging has the potential to be a noninvasive adjunct diagnostic tool for gingival inflammation, and may help assess the stage of the disease and ultimately limit periodontal disease occurrence; taking into consideration the limits of this study.

scholarly journals Using the method of renormalization with limitation for medical ultrasound image processing.

2020 ◽  
Vol 2020 (10) ◽  
Author(s):  
A.V. Kokoshkin ◽  
Keyword(s):  
Image Processing ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Bilateral Filtering ◽  
Ultrasound Image Processing ◽  
Images Processing

This article proposes the application of the technique of combining the modernized method of renormalization with limitation with subsequent bilateral filtering to improve the quality of medical ultrasound images. Processing according to this algorithm increases the overall contrast of the image, smoothes out speckle noise and makes it possible to cope well with determining the localization of significant objects. The presented results indicate a significant improvement in the quality of ultrasound images, which can serve as an auxiliary tool for medical workers when clarifying the diagnosis.

Ultrasound Medical Image Denoising Using Threshold Based Wavelet Transformation Method

2020 ◽  
Vol 10 (8) ◽  
pp. 1825-1830 ◽  
Author(s):  
C. Kumar ◽  
R. Prakash
Keyword(s):  
Image Processing ◽  
Image Denoising ◽  
Ultrasound Imaging ◽  
Wavelet Transformation ◽  
Transformation Method ◽  
Experimental Result ◽  
Ultrasound Images ◽  
Baseline Phase ◽  
Noise Factors

Ultrasound imaging is most commonly used and secure medical diagnostic approach its low cost, noninvasive nature of real time image construction. However because of signal dependant noise existence, ultrasound imaging gets degraded: A baseline phase in image processing is removing diverse noise types from image. Noise sources of image generally occur during storage, transmission and image acquisition. Image denoising is an issue determined in diverse computer vision and image processing crisis. There are diverse prevailing approaches to denoise image. The significant property of finest denoising of an image model has to remove noise while preserving edges. For wavelet thresholding paradigm, Fisz transformation method is brought-in in the current work. Furthermore, it has problem with poor denoising performance and hence the quality of image is minimized considerably. In this paper, Improved Threshold based Wavelet Transformation Method (ITWTM) is suggested to rectify above mentioned crisis, to enhance the better denoising images, the soft threshold method is introduced. To enhance visual quality of noisy image, it simply changes coefficients with help of softthresholding method. Speckle noise, additive noise, Gaussian noise and multiplicative noise factors affect the ultrasound images, which minimize the image quality and effects the human interpretation. So, ITWTM helps to minimize the noise rate considerably for the provided US image. The experimental result confirms that the proposed ITWTM provides better performance with respect to higher PSNR, SSIM and lower MSE, execution time rather than the previous Fisz transformation and DWT methods.

scholarly journals Refinement for Ocular Ultrasound Images Quality by Utilizing Combination of Enhancement Techniques

2016 ◽  
Vol 9 (3) ◽  
pp. 37
Author(s):  
Zinah Rajab Hussein ◽  
Zaid Rajab Hussein
Keyword(s):  
Wavelet Coefficient ◽  
Low Cost ◽  
Ultrasound Image ◽  
Mapping Function ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Diagnostic Modality ◽  
Ocular Ultrasound ◽  
Wide Availability

Ultrasound has been used as a diagnostic modality for many intraocular diseases, due its safety, low cost, real time and wide availability. Unfortunately, ultrasound images suffer from speckle artifact that are tissue dependent. In this work, we will offer a method to reduce speckle noise and improve ultrasound image to raise the human diagnostic performance. This method combined undecimated wavelet transform with a wavelet coefficient mapping function: where UDWT used to eliminate the noise and a wavelet coefficient mapping function used to enhance the contrast of denoised images obtained from the first component. This methods can be used not only as a means for improving visual quality of medical images but also as a preprocessing module for computer-aided detection/diagnosis systems to improve the performance of screening and detecting regions of interest in images. The proposed method is experimentally evaluated via 60 ultrasound images of eye. It is demonstrated that the proposed method can further improve the image quality of ocular ultrasound; the results reveal the effectiveness and superiority of the proposed method.

scholarly journals Effects of various De-Speckling Filters on Brachial Plexus Ultrasound Imaging

2019 ◽  
Vol 8 (2) ◽  
pp. 5058-5065
Keyword(s):  
Brachial Plexus ◽  
Ultrasound Imaging ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Important Process

Medical Ultrasound images are generally corrupted by Speckle noise. It deteriorates the quality of ultrasound imaging and video that makes it difficult to observe visually. Because of which resolution and contrast of the image is reduced. Despeckling of medical US images is an important process for diagnostic of disease. In this paper effect of various existing despeckling filter on ultrasound images has been studied. All the filters have been implemented in a framework and result are observed in the form of various parameters such as GAE, MSE, SNR, SRMSE, PSNR, UIQI, SSIM, AD, SC, MD. The results obtained have been used for statistically comparing the performance of the filters. It is also analyzed that which type of filters are more suited for particular type of images, noise and other conditions. This will also provide guidelines for the researchers for designing of new filters in future.

scholarly journals The Biopsy of Boar Testes Using Ultrasonographic Examination

2014 ◽  
Vol 37 (1) ◽  
pp. 69-74
Author(s):  
Laima Liepa ◽  
Zigmunds Bruveris ◽  
Mara Mangale ◽  
Ilmars Duritis ◽  
Vita Antane ◽  
...  
Keyword(s):  
Reproductive System ◽  
Needle Biopsy ◽  
Ultrasound Guidance ◽  
Ultrasound Image ◽  
Testicular Biopsy ◽  
Skin Incision ◽  
Ultrasound Images ◽  
Live Animal ◽  
Ultrasonographic Examination

Abstract The biopsy of live animal testes is an important clinical manipulation to control spermatogenesis and reproductive system pathologies. The aim was to develop a method of boar testes biopsy using a biopsy gun with ultrasound guidance and to investigate the influence of this procedure on the boar testes parenchyma and quality of ejaculate. The biopsy was carried out in six 8-month-old boars. Fourteen days prior to and 21 days after biopsy, the quality of ejaculate was examined (weight of ejaculate; concentration and motility of spermatozoa) with a seven-day intervals. Ultrasound images of the testes parenchyma were recorded three times: directly before and 15 minutes after the biopsy, then 21 days after the procedure. The testes biopsies of generally anesthetized boars were performed with the biopsy gun for needle biopsy with a 12cm long, disposable 16-gauge needle 1.8mm in diameter (Vitesse) through 1cm skin incision in the depth of 1.2-1.6cm of parenchyma. Fifteen minutes after the biopsy, macroscopic injures of the parenchyma of all the boar testes were not detected in the ultrasound image. Twenty one days after biopsy, the hyperechogenic line 0.1-0.2cm in diameter was seen in the testes parenchyma of six boars in the depth of 1.2-1.6cm. The biopsy of boar testes did not influence the quality of boars ejaculate. The ultrasonographic examination of boar testicles before the biopsy reduced possibilities to traumatize large blood vessels of the testes. A perfect boar testicular biopsy was easy to perform using ultrasonographic examination in the pigsty conditions.

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