Assessment of Homodyned K Distribution Modeling Ultrasonic Speckles from Scatterers with Varying Spatial Organizations

Hu, Xiao; Zhang, Yufeng; Deng, Li; Cai, Guanghui; Zhou, Yi; Zhang, Kexin; Zhang, Junhua

doi:10.1155/2017/8154780

Cited by 9 publications

(13 citation statements)

References 33 publications

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“…First, the authors in Hu et al 39 adapted a numerical integration function quadgk in the MATLAB platform to calculate the PDF of the HK distribution. Whereas the authors in Wang et al 40 considered that significant oscillation is produced by the Bessel function contained in the PDF of HK distribution, therefore they used an advanced CAPSO algorithm to calculate the PDF of the HK distribution.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Therefore, we need to further explore a method that can find a point that maximizes the log-likelihood equation (at least in some bounded domain) and always converges. In addition, relevant contents such as the range of the various functions and the setting of the initial values in an implementation have not been sufficiently discussed in the article Hu et al 39 and Wang et al 40…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…4 Thus, as a classical parameter estimation method, the MLE has been used to estimate the parameters of the HK distribution. Hu et al 39 first used MLE to estimate parameters of HK distribution to assess the physical meanings of parameters and goodness of fit of HK distribution for ultrasound envelope data from scatterer distributions with wide-varying spatial organizations. They used a high-order global adaptive Gauss-Kronrod quadrature method to calculate the probability density function (PDF) of the HK distribution, and then used the Newton-Raphson method to numerically solve the log-likelihood equation.…”

Section: Introductionmentioning

confidence: 99%

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An Improved Parameter Estimator of the Homodyned K Distribution Based on the Maximum Likelihood Method for Ultrasound Tissue Characterization

Liu

Zhang

et al. 2022

Ultrason Imaging

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The homodyned K distribution (HK) can generally describe the ultrasound backscatter envelope statistics distribution with parameters that have specific physical meaning. However, creating robust and reliable HK parameter estimates remains a crucial concern. The maximum likelihood estimator (MLE) usually yields a small variance and bias in parameter estimation. Thus, two recent studies have attempted to use MLE for parameter estimation of HK distribution. However, some of the statements in these studies are not fully justified and they may hinder the application of parameter estimation of HK distribution based on MLE. In this study, we propose a new parameter estimator for the HK distribution based on the MLE (i.e., MLE1), which overcomes the disadvantages of conventional MLE of HK distribution. The MLE1 was compared with other estimators, such as XU estimator (an estimation method based on the first moment of the intensity and tow log-moments) and ANN estimator (an estimation method based on artificial neural networks). We showed that the estimations of parameters α and k are the best overall (in terms of the relative bias, normalized standard deviation, and relative root mean squared errors) using the proposed MLE1 compared with the others based on the simulated data when the sample size was N = 1000. Moreover, we assessed the usefulness of the proposed MLE1 when the number of scatterers per resolution cell was high (i.e., α up to 80) and when the sample size was small (i.e., N = 100), and we found a satisfactory result. Tests on simulated ultrasound images based on Field II were performed and the results confirmed that the proposed MLE1 is feasible and reliable for the parameter estimation from the ultrasonic envelope signal. Therefore, the proposed MLE1 can accurately estimate the HK parameters with lower uncertainty, which presents a potential practical value for further ultrasonic applications.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Improved Parameter Estimator of the Homodyned K Distribution Based on the Maximum Likelihood Method for Ultrasound Tissue Characterization

Liu

Zhang

et al. 2022

Ultrason Imaging

Self Cite

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show abstract

“…However, the application of the HK model has been limited due to the analytical complexity in estimating the parameters. Currently, there are moment-based estimators [37,[39][40][41] and numerical methods [42] for estimating HK parameters. Moment-based estimators include (i) the estimator that uses the signal-to-noise ratio (SNR) and the skewness based on the first three integer moments of the intensity, which is the square of the envelope (this method is termed "FTM") [37,39], (ii) a level-curve method that uses the SNR, skewness, and kurtosis based on the fractional moments of the envelope (this method is termed "RSK") [40], and (iii) an estimation method based on the first moment of the intensity and two log-moments, namely X-and U-statistics (this method is termed "XU") [41].…”

Section: Ultatrasound Homodyned-k Imagingmentioning

confidence: 99%

Hepatic Steatosis Assessment Using Quantitative Ultrasound Parametric Imaging Based on Backscatter Envelope Statistics

Zhou

Zhang

et al. 2019

Applied Sciences

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Hepatic steatosis is a key manifestation of non-alcoholic fatty liver disease (NAFLD). Early detection of hepatic steatosis is of critical importance. Currently, liver biopsy is the clinical golden standard for hepatic steatosis assessment. However, liver biopsy is invasive and associated with sampling errors. Ultrasound has been recommended as a first-line diagnostic test for the management of NAFLD. However, B-mode ultrasound is qualitative and can be affected by factors including image post-processing parameters. Quantitative ultrasound (QUS) aims to extract quantified acoustic parameters from the ultrasound backscattered signals for ultrasound tissue characterization and can be a complement to conventional B-mode ultrasound. QUS envelope statistics techniques, both statistical model-based and non-model-based, have shown potential for hepatic steatosis characterization. However, a state-of-the-art review of hepatic steatosis assessment using envelope statistics techniques is still lacking. In this paper, envelope statistics-based QUS parametric imaging techniques for characterizing hepatic steatosis are reviewed and discussed. The reviewed ultrasound envelope statistics parametric imaging techniques include acoustic structure quantification imaging, ultrasound Nakagami imaging, homodyned-K imaging, kurtosis imaging, and entropy imaging. Future developments are suggested.

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“…Nonhomogeneous tissue is usually simulated by discrete digital phantoms based on the small scatterers distributed in space. The proper setting of scatterer maps is essential for the realistic resulting image of ultrasonic wave interference (speckle) pattern [ 15 ]. The mean scatterer spacing (MCS) for different tissues was reviewed in [ 16 ] showing the potential to simulate tissue microstructure by fitting the MCS parameter.…”

Section: Introductionmentioning

confidence: 99%

Main Uncertainties in the RF Ultrasound Scanning Simulation of the Standard Ultrasound Phantoms

Makūnaitė

Jurkonis

Lukoševičius

et al. 2021

Sensors

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Ultrasound echoscopy technologies are continuously evolving towards new modalities including quantitative parameter imaging, elastography, 3D scanning, and others. The development and analysis of new methods and algorithms require an adequate digital simulation of radiofrequency (RF) signal transformations. The purpose of this paper is the quantitative evaluation of RF signal simulation uncertainties in resolution and contrast reproduction with the model of a phased array transducer. The method is based on three types of standard physical phantoms. Digital 3D models of those phantoms are composed of point scatterers representing the weak backscattering of the background material and stronger backscattering from inclusions. The simulation results of echoscopy with sector scanning transducer by Field II software are compared with the RF output of the Ultrasonix scanner after scanning standard phantoms with 2.5 MHz phased array. The quantitative comparison of axial, lateral, and elevation resolutions have shown uncertainties from 9 to 22% correspondingly. The echoscopy simulation with two densities of scatterers is compared with contrast phantom imaging on the backscattered RF signals and B-scan reconstructed image, showing that the main sources of uncertainties limiting the echoscopy RF signal simulation adequacy are an insufficient knowledge of the scanner and phantom’s parameters. The attempt made for the quantitative evaluation of simulation uncertainties shows both problems and the potential of echoscopy simulation in imaging technology developments. The analysis presented could be interesting for researchers developing quantitative ultrasound imaging and elastography technologies looking for simulated raw RF signals comparable to those obtained from real ultrasonic scanning.

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Assessment of Homodyned K Distribution Modeling Ultrasonic Speckles from Scatterers with Varying Spatial Organizations

Cited by 9 publications

References 33 publications

An Improved Parameter Estimator of the Homodyned K Distribution Based on the Maximum Likelihood Method for Ultrasound Tissue Characterization

An Improved Parameter Estimator of the Homodyned K Distribution Based on the Maximum Likelihood Method for Ultrasound Tissue Characterization

Hepatic Steatosis Assessment Using Quantitative Ultrasound Parametric Imaging Based on Backscatter Envelope Statistics

Main Uncertainties in the RF Ultrasound Scanning Simulation of the Standard Ultrasound Phantoms

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