Elastographic Imaging Using Staggered Strain Estimates

2002 ◽  
Vol 24 (4) ◽  
pp. 229-245 ◽  
Author(s):  
S. Srinivasan ◽  
J. Ophir ◽  
S.K. Alam

Conventional techniques in elastography estimate strain as the gradient of the displacement estimates obtained through crosscorrelation of pre- and postcompression rf A-lines. In these techniques, the displacements are estimated over overlapping windows and the strains are estimated as the gradient of the displacement estimates over adjacent windows. The large amount of noise at high window overlaps may result in poor quality elastograms, thus restricting the applicability of conventional strain estimation techniques to low window overlaps, which, in turn, results in a small number of pixels in the image. To overcome this restriction, we propose a multistep strain estimation technique. It computes the first elastogram using nonoverlapped windows. In the next step, the data windows are shifted by a small distance (small fraction of window size) and another elastogram is produced. This is repeated until the cumulative shift equals/exceeds the window size and all the elastograms are staggered to produce the final elastogram. Simulations and experiments were performed using this technique to demonstrate significant improvement in the elastographic signal-to-noise ratio ( SNRe) and the contrast-to-noise ratio ( CNRe) at high window overlaps over conventional strain estimation techniques, without noticeable loss of spatial resolution. This technique might be suitable for reducing the algorithmic noise in the elastograms at high window overlaps.

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1139 ◽  
Author(s):  
Kai Yang ◽  
Zhitao Huang ◽  
Xiang Wang ◽  
Fenghua Wang

Signal-to-noise ratio (SNR) is a priori information necessary for many signal processing algorithms or techniques. However, there are many problems exsisting in conventional SNR estimation techniques, such as limited application range of modulation types, narrow effective estimation range of signal-to-noise ratio, and poor ability to accommodate non-zero timing offsets and frequency offsets. In this paper, an SNR estimation technique based on deep learning (DL) is proposed, which is a non-data-aid (NDA) technique. Second and forth moment (M2M4) estimator is used as a benchmark, and experimental results show that the performance and robustness of the proposed method are better, and the applied ranges of modulation types is wider. At the same time, the proposed method is not only applicable to the baseband signal and the incoherent signal, but can also estimate the SNR of the intermediate frequency signal.


2020 ◽  
Author(s):  
fu-zhong bai ◽  
Jiayi Chen ◽  
Xiaojuan Gao ◽  
Yongxiang Xu

Abstract In the accuracy measurement of phase from interferometers with adjustable fringe visibility, it needs to estimate the visibility of experimental patterns so as to obtain the interference patterns with the maximum visibility. We develop the Fourier-polar transform and combine the directional projection to estimate the global visibility of carrier fringe pattern. The technique is especially used for low-quality fringe pattern such as low contrast and low (signal to noise ratio) SNR that often appear in the interferometric experiment. An illustrative experiment based on the radial shearing interferometer is given. Results generated from this technique are compared with the derived values from theoretical model, and exemplary agreement between both is demonstrated.


Author(s):  
G.Manmadha Rao* ◽  
Raidu Babu D.N ◽  
Krishna Kanth P.S.L ◽  
Vinay B. ◽  
Nikhil V.

Removal of noise is the heart for speech and audio signal processing. Impulse noise is one of the most important noise which corrupts different parts in speech and audio signals. To remove this type of noise from speech and audio signals the technique proposed in this work is signal dependent rank order mean (SD-ROM) method in recursive version. This technique is used to replace the impulse noise samples based on the neighbouring samples. It detects the impulse noise samples based on the rank ordered differences with threshold values. This technique doesn’t change the features and tonal quality of signal. Rank ordered differences is used for detecting the impulse noise samples in speech and audio signals. Once the sample is detected as corrupted sample, that sample is replaced with rank ordered mean value and this rank ordered mean value depends on the sliding window size and neighbouring samples. This technique shows good results in terms of signal to noise ratio (SNR) and peak signal to noise ratio (PSNR) when compared with other techniques. It mainly used for removal of impulse noises from speech and audio signals.


2018 ◽  
Vol 51 (1-2) ◽  
pp. 27-37 ◽  
Author(s):  
Konstantinos Marmarokopos ◽  
Dimitrios Doukakis ◽  
George Frantziskonis ◽  
Markos Avlonitis

A method for detecting leaks in plastic water supply pipes through analysis of the pipe’s surface vibration using a high signal-to-noise ratio accelerometer is proposed and examined. The method involves identification of the changes in vibration frequencies caused on the pipe by the leak and is developed from and examined with respect to detailed experiments. The results are promising, showing that leak detection in plastic pipes is possible provided that the sensor is placed at a small distance from the leak, since wave attenuation in plastic is strong. The results indicate that the methodology has the potential to be a new and competitive type of mobile leak detection system.


1993 ◽  
Vol 15 (3) ◽  
pp. 181-204 ◽  
Author(s):  
J.T.M. Verhoeven ◽  
J.M. Thijssen

An objective measure (Lesion Signal-to-Noise Ratio) quantifying the detectability of lesions in echographic images was employed. This measure was used to determine the performance of digital speckle reduction filters, which were applied to computer simulated ultrasound B-mode images. One linear (mean filter) and two nonlinear filters (median and L2-mean filters) have been investigated. A comparison was made between fixed and adaptive versions of these filters. The influence of the size of the filter window on the Lesion Signal-to-Noise Ratio was systematically investigated. Also, the effect of the shape of the filter window is illustrated. The difference in performance of the linear and nonlinear filters was found to be small. Adaptive filters did not perform significantly better than fixed filters. The maximum improvement of lesion detectability was in the order of 40 percent. The choice of a correct window size was critical. For all types of filters, an optimum window size appeared to be present in the curves relating the Lesion Signal-to-Noise Ratio to this size.


2012 ◽  
Vol 58 (3) ◽  
pp. 273-278 ◽  
Author(s):  
Taleb Moazzeni ◽  
Amei Amei ◽  
Jian Ma ◽  
Yingtao Jiang

Abstract Signal-to-noise ratio (SNR) information is required in many communication receivers and their proper operation is, to a large extent, related to the SNR estimation techniques they employ. Most of the available SNR estimators are based on approaches that either require large observation length or suffer from high computation complexity. In this paper, we propose a low complexity, yet accurate SNR estimation technique that is sufficient to yield meaningful estimation for short data records. It is shown that our estimator is fairly close to the (CRLB) for high SNR values. Numerical results also confirm that, in terms of convergence speed, the proposed technique outperforms the popular moment based method, M2M4


2021 ◽  
pp. 4439-4452
Author(s):  
Noor H. Resham ◽  
Heba Kh. Abbas ◽  
Haidar J. Mohamad ◽  
Anwar H. Al-Saleh

    Ultrasound imaging has some problems with image properties output. These affects the specialist decision. Ultrasound noise type is the speckle noise which has a grainy pattern depending on the signal. There are two parts of this study. The first part is the enhancing of images with adaptive Weiner, Lee, Gamma and Frost filters with 3x3, 5x5, and 7x7 sliding windows. The evaluated process was achieved using signal to noise ratio (SNR), peak signal to noise ratio (PSNR), mean square error (MSE), and maximum difference (MD) criteria. The second part consists of simulating noise in a standard image (Lina image) by adding different percentage of speckle noise from 0.01 to 0.06. The supervised classification based minimum distance method is used to evaluate the results depending on selecting four blocks located at different places on the image. Speckle noise was added with different percentage from 0.01 to 0.06 to calculate the coherent noise within the image. The coherent noise was concluded from the slope of the standard deviation with the mean for each noise. The results showed that the additive noise increased with the slide window size, while multiplicative noise did not change with the sliding window nor with increasing noise ratio. Wiener filter has the best results in enhancing the noise.


2020 ◽  
Vol 10 (5) ◽  
pp. 1057-1068
Author(s):  
Hui Peng ◽  
Juhong Tie ◽  
Dequan Guo

Conventional ultrasound strain imaging usually only calculates the axial strain. Although axial strain is the main component of two dimensional strain field, lateral displacement and strain estimation can provide additional information of human mechanical properties. Shear strain and Poisson’s ratio can be estimated by using lateral strain estimation technique. Low lateral sampling rate and decorrelation noise of lateral radio frequency (RF) signal caused by axial displacement motion increase the difficulty of lateral strain estimation. Subband division technique is to divide a broadband signal into several narrowband signals. In this paper, the application of subband division technique in axial and lateral strain estimation is studied, and an iterative method for estimating axial and lateral strains is proposed based on subband technique. The subband division of this method is carried out along the axial direction, so that the bandwidth of the lateral subband signal is maintained and the quality of the lateral sub strain image is not reduced. In this paper, the number of subbands is three; the compounded lateral strain image is obtained by superimposing these sub strain images on the average. In each iteration, the temporal stretching technique is used to align the axial and lateral RF signals by using the axial and lateral displacement estimation information, which reduces the decorrelation noise of the RF signals. The length of temporal stretching window decreases with the number of iterations, so as to gradually improve the accuracy of temporal stretching. The phase zero algorithm is used to estimate the axial and lateral displacements. The effectiveness of this method is tested by simulations. The simulation results show that the elastographic signal-to-noise ratio (SNRe) of lateral strain image is increased by about 50%, the elastographic contrast noise ratio (CNRe) of lateral strain image is increased by about 120%, the SNRe of axial strain image is increased by about 4%, the CNRe of axial strain image is increased by 8%, and the signal-to-noise ratio of Poisson’s ratio image is increased by about 40%.


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