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.

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).

Denoising Ultrasound Medical Images

2015 ◽  
Vol 5 (1) ◽  
pp. 1-14
Author(s):  
A.S.C.S.Sastry ◽  
P.V.V.Kishore MIEE ◽  
Ch.Raghava Prasad ◽  
M.V.D.Prasad
Keyword(s):  
Image Quality ◽  
Medical Images ◽  
Ultrasound Image ◽  
Similarity Index ◽  
Speckle Noise ◽  
Inverse Transformation ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Soft Thresholding

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 Novel image enhancement approaches for despeckling in ultrasound images for fibroid detection in human uterus

2021 ◽  
Vol 11 (1) ◽  
pp. 399-410
Author(s):  
Kaitheri Thacharedath Dilna ◽  
Duraisamy Jude Hemanth
Keyword(s):  
Image Processing ◽  
Signal To Noise Ratio ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Speckle Reduction ◽  
Ultrasound Images ◽  
Signal To Noise ◽  
Statistical Measures ◽  
Noise Ratio ◽  
Scanned Images

Abstract Ultrasonography is an extensively used medical imaging technique for multiple reasons. It works on the basic theory of echoes from the tissues under consideration. However, the occurrence of signal dependent noise such as speckle destroys utility of ultrasound images. Speckle noise is subject to the composition of image tissue and parameters of image. It reduces the effectiveness of many image processing steps and decreases human perception of fine details form ultrasound images. In many medical image processing methods, despeckling is used as the preprocessing step before segmentation and feature extraction. Many speckle reduction filters are proposed but while combining many techniques some speckle diagnostic information should be preserved. Removal of speckle noise from ultrasound image by preserving edges and added features is a great challenging task in ultrasound image restoration. This paper aims at a comprehensive description and comparison of reduction of speckle noise of ultrasound fibroid image. Many filters are applied on ultrasound scanned images and the performance is marked in terms of some statistical measures. Even though several despeckling filters are there for speckle reduction, all are not good for ultrasound scanned images. A comparison of quality measures such as mean square error, peak signal-to-noise ratio, and signal-to-noise ratio is done in ultrasound images in despeckling.

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 Ultrasound Image Enhancement Using Structure-Based Filtering

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Shyh-Kuang Ueng ◽  
Cho-Li Yen ◽  
Guan-Zhi Chen
Keyword(s):  
Image Processing ◽  
Diffusion Tensor ◽  
Median Filter ◽  
Ultrasound Image ◽  
Underlying Structure ◽  
Ultrasound Images ◽  
Test Results ◽  
Classification Result ◽  
Linear Filters ◽  
Ultrasound Image Processing

Ultrasound images are prone to speckle noises. Speckles blur features which are essential for diagnosis and assessment. Thus despeckling is a necessity in ultrasound image processing. Linear filters can suppress speckles, but they smooth out features. Median filter based despeckling algorithms produce better results. However, they may produce artifact patterns in the resulted images and oversmooth nonuniform regions. This paper presents an innovative despeckle procedure for ultrasound images. In the proposed method, the diffusion tensor of intensity is computed at each pixel at first. Then the eigensystem of the diffusion tensor is calculated and employed to detect and classify the underlying structure. Based on the classification result, a feasible filter is selected to suppress speckles and enhance features. Test results show that the proposed despeckle method reduces speckles in uniform areas and enhances tissue boundaries and spots.

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 Fractional Calculus and Fuzzy Rule Based Filter for Despeckling the Medical Images

2018 ◽  
Vol 7 (4.10) ◽  
pp. 685
Author(s):  
Nageswari P ◽  
Rajan S ◽  
Manivel K
Keyword(s):  
Fractional Order ◽  
Medical Image ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Medical Image Analysis ◽  
Ultrasound Image ◽  
Fuzzy Rule ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Medical Ultrasound

Medical ultrasound imaging plays an important role in diagnosis of various complicated disorders. But, these ultrasound images are intrinsically degraded with speckle noise which harshly affects the image visual qualities and essential particulars. Hence, denoising is an unavoidable process in medical image processing.  In this paper, a new despeckling technique is presented for denoising the medical ultrasound images by employing fuzzy technique on co-efficient of variation and fractional order integration filter. The proposed technique has two steps. During first step, the noisy image pixels are classified into three regions by using fuzzy technique on co-efficient of variation and consequently, the proposed technique adaptively employs appropriate filters on the grouped pixels to reduce noise in the ultrasound image. In the second step, to obtain an effective denoising image, the fractional order integration filter is applied on the resulting image of step 1. The performance of the proposed technique is tested on various medical images in terms of Peak signal to noise ratio and speckle suppression index quality measures. Experimental results reveal that the proposed despeckling technique can efficiently reduce the speckle noise, protect the edges and preserves any other important structural details of an image. It is suggested that the proposed technique is employed as a preprocessing tool for medical image analysis and diagnosis. 

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