Spectral correlation in ultrasonic pulse echo signal processing

Donohue, Kevin D.; Bressler, J.M.; Varghese, Tomy; Bilgutay, N.M.

doi:10.1109/58.251281

Cited by 36 publications

(11 citation statements)

References 11 publications

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“…This estimator has been widely used in many quantitative ultrasound applications. 19;20;56;57;67 Multitaper method (MTM): A set of K GS estimates is obtained from the Fourier transforms of the RF echosignal segment when separately tapered by K DPSS. The final GS estimate is given by the weighted average of the K individual estimates.…”

Section: Methodsmentioning

confidence: 99%

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Analysis of Coherent and Diffuse Scattering Using a Reference Phantom

Rosado‐Mendez

Drehfal

Zagzebski

et al. 2016

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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The estimation of many spectral-based, Quantitative Ultrasound parameters assumes that backscattered echo signals are from a stationary, incoherent scattering process. The accuracy of these assumptions in real tissue can limit the diagnostic value of these parameters and the physical insight about tissue microstructure they can convey. This work presents an empirical decision test to determine the presence of significant coherent contributions to echo signals and whether they are caused by low scatterer number densities or the presence of specular reflectors or scatterers with periodic spacing. This is achieved by computing parameters from echo signals that quantify stationary or non-stationary features related to coherent scattering, and then comparing their values to thresholds determined from a reference material providing diffuse scattering. The paper first presents a number of parameters with demonstrated sensitivity to coherent scattering and describes criteria to select those with highest sensitivity using simulated and phantom-based echo data. Results showed that the echo amplitude signal-to-noise ratio and the multitaper generalized spectrum were the parameters with highest sensitivity to coherent scattering with stationary and non-stationary features, respectively. These parameters were incorporated into the reference-based decision test, which successfully identified regions in simulated and tissue-mimicking phantoms with different incoherent and coherent scattering conditions. When scatterers with periodic organization were detected, the combination of stationary and non-stationary analysis permitted the estimation of the mean spacing below and above the resolution limit imposed by the pulse size. Preliminary applications of this algorithm to human cervical tissue ex vivo showed correspondence between regions of B-mode images showing bright reflectors, tissue interfaces, and hypoechoic regions with regions classified as specular reflectors and low scatterer number density. These results encourage further application of the algorithm to more structurally complex phantoms and tissue.

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Section: Methodsmentioning

confidence: 99%

“…63 Most importantly, the presence of coherent scattering shows up as significant non-zero values outside the 0MHz peak. 19;56;67 The useful frequency ranges of the GS are determined by the available signal bandwidth.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Coherent and Diffuse Scattering Using a Reference Phantom

Rosado‐Mendez

Drehfal

Zagzebski

et al. 2016

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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“…In this work we define CDR as the ratio of the average energies for diffuse and coherent scatterers as our model is based on a two-component scatter model in which diffuse component represents randomly located, unresolvable scatterers, and coherent component represents nonrandomly distributed, resolvable scatterers. Note that the CDR here is referred to as signal-to-noise ratio (SNR) in some other studies [9], [21], [29]. However, in order to avoid confusion with the concept of noise as an additive component independent of the scatterers, we use CDR instead of SNR.…”

Section: Simulation Of Reflection Of Rf Echo From Breast Ductsmentioning

confidence: 97%

Classification of simulated hyperplastic stages in the breast ducts based on ultrasound RF echo

Taslidere

Cohen

Γεωργίου

2008

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Visual inspection of ultrasound is diagnostically limited for characterizing breast tissue, in particular when it comes to visually detecting hyperplasia that forms in the ducts at its early formation (at submillimeter resolution) stages. It can, of course, be seen using biopsies. But this will not be done unless the areas have been flagged using noninvasive modalities. The aim of this paper is to draw to the attention of the medical community (albeit through simulations) that the continuous wavelet transform decomposition (CWTD) that was proven in vivo for tissue characterization before has the potential to flag out simulated hyperplasia data at submillimeter resolutions. And it might be an excellent candidate for detecting in vivo hyperplastic changes in the breast. To the best of our knowledge, this is the first attempt at studying the potential of detecting cell growth in breast ducts using ultrasound. The stochastic decomposition model (the CWTD) of the RF echo with its coherent and diffuse components, yields image parameters that correlate closely with the structural parameters of the (simulated) hyperplastic stages of the breast tissue. The discrimination power of the various parameters is studied under a host of conditions, such as varying resolution, depth, and coherent to diffuse energy ratio (CDR) values using a point-scatterer model simulator that mimics epithelium hyperplastic growth in the breast ducts. These are shown to be useful for detecting the various types of simulated hyperplastic data. Careful analysis shows that three parameters, in particular the number of coherent scatterers, the Rayleigh scattering degree, and the energy of the diffuse scatterers, are most sensitive to variations in the hyperplastic simulated data. And they show very high ability to discriminate between various stages of simulated hyperplasia, even in cases of low resolution and low CDR values. Using the area under the receiver operating characteristics (ROC) curve (A(z)) as the performance metric, values of A(z) > 0.942 are obtained when discriminating between stages for resolution 0.948 for different duct densities.

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“…(i) x(n) is the nonpredictable part given by x(n) = 3w(n -s) + w(n) (4) Under the invertibility condition,17 x(n) is expressed as x(n) = ax(n -s) + w(n) = 1(n) + w(n) (5) where a-E{y(n)w(n-s)} a<oo (6) { w(n)} is white innovation sequence with zero mean and variance 2; (ii) p(n) is completely predictable (i.e., it is either deterministic or stochastic but with a prediction error of 0, i.e., p(n) = sP(fl_ s) =(n) (7) (iii) p(n) is uncorrelated with w(n), i.e., E{p(i)w(s)} = 0 for all t and s. This implies that p(n) and x(n) are orthogonal, i.e., E{p(t)x(s)} = 0 for all i and s.…”

Section: Wold Decomposition Of the Rf Echomentioning

confidence: 99%

<title>Can a machine outperform a clinician in interpreting ultrasound images?</title>

Cohen

Γεωργίου

1996

SPIE Proceedings

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This paper deals with a method of detecting and estimating the scatterer spacing between the regularly spaced resolvable coherent scatterers in tissue. Scatterer spacing has been successfully used in classifying tissue structure, in differentiating between normal and cirrhotic liver, and in detecting diffuse liver disease. This paper presents a Wold decomposition of the radio frequency (RF) field into its diffused and coherent components from which maximum likelihood estimates (MLE) or minimum mean square error (MMSE) estimates of the scattering spacing are easily computed. The MLE are efficient and for relatively long record are unbiased. They result in accurate estimates in low signal-to-noise (SNR) ratios. Unfortunately, they require nonlinear minimization and knowledge of the probability density associated with the RF backscatter echo. The MMSE estimates, on the other hand, are computational simple, yield unique closed form solutions, do not require a priori knowledge of the probability distribution function of the backscatter echo, and result in accurate estimates in low signal-to-noise (SNR) ratios. The paper also presents an unbiased decision rule to detect whether or not an RF echo exhibits any specular scattering relative to the wavelength of the interrogating ultrasonic pulse. The approach has been tried on simulations as well as on in vivo scans of liver data, and appears to perform well.

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Spectral correlation in ultrasonic pulse echo signal processing

Cited by 36 publications

References 11 publications

Analysis of Coherent and Diffuse Scattering Using a Reference Phantom

Analysis of Coherent and Diffuse Scattering Using a Reference Phantom

Classification of simulated hyperplastic stages in the breast ducts based on ultrasound RF echo

<title>Can a machine outperform a clinician in interpreting ultrasound images?</title>

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