A novel power spectrum calculation method using phase-compensation and weighted averaging for the estimation of ultrasound attenuation

Heo, Seo Weon; Kim, Hyungsuk

doi:10.1016/j.ultras.2009.12.004

Cited by 4 publications

(2 citation statements)

References 38 publications

(44 reference statements)

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“…1,[5][6][7][8][9][10] Most methods for estimating α(f) and σ b (f) rely on a spectral analysis of radiofrequency (RF) echo signals by computing their power spectral density. [11][12][13][14][15][16][17][18][19][20][21] Estimations of α(f) and σ b (f) are based on the assumption that the power spectral density quantifies the expected energy resulting from the incoherent superposition of backscattered waves from scatterers randomly distributed within the acoustic pulse volume. The power spectral density is usually computed as the average of a set of periodograms from gated segments of RF echo signals from adjacent acoustic scanlines within an estimation window.…”

Section: Introductionmentioning

confidence: 99%

Task-Oriented Comparison of Power Spectral Density Estimation Methods for Quantifying Acoustic Attenuation in Diagnostic Ultrasound Using a Reference Phantom Method

et al. 2013

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Reported here is a phantom-based comparison of methods for determining the power spectral density of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)=α0fβ, was estimated using a reference phantom method. The power spectral density as estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error. For parameter estimation regions larger than ~34 pulse lengths (~1cm for this experiment), an overall power-law fit error of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here the multitaper method reduced the standard deviation of the α0 and β estimates compared to those using the other techniques. Results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound.

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Section: Introductionmentioning

confidence: 99%

Task-Oriented Comparison of Power Spectral Density Estimation Methods for Quantifying Acoustic Attenuation in Diagnostic Ultrasound Using a Reference Phantom Method

et al. 2013

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“…Therefor, time delay can be estimated by searching the abscissa of peak 𝑛 * 𝑐 corresponding to Eq. ( 2) [8] and presented as:…”

Section: Problem Statementmentioning

confidence: 99%

A New Subsample Time Delay Estimation Algorithm for LFM-Based Detection

Yang

et al. 2023

IEICE Trans. Fundamentals

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This paper investigated a Subsample Time delay Estimation (STE) algorithm based on the amplitude of cross-correlation function to improve the estimation accuracy. In this paper, a rough time delay estimation is applied based on traditional cross correlator, and a fine estimation is achieved by approximating the sampled cross-correlation sequence to the amplitude of the theoretical cross-correlation function for linear frequency modulation (LFM) signal. Simulation results show that the proposed algorithm outperforms existing methods and can effectively improve time delay estimation accuracy with the complexity comparable to the traditional crosscorrelation method. The theoretical Cramér-Rao Bound (CRB) is derived, and simulations demonstrate that the performance of STE can approach the boundary. Eventually, four important parameters discussed in the simulation to explore the impact on Mean Squared Error (MSE).

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Evaluation method of the degree of red blood cell aggregation considering ultrasonic propagation attenuation by analyzing ultrasonic backscattering properties

et al. 2021

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A novel power spectrum calculation method using phase-compensation and weighted averaging for the estimation of ultrasound attenuation

Cited by 4 publications

References 38 publications

Task-Oriented Comparison of Power Spectral Density Estimation Methods for Quantifying Acoustic Attenuation in Diagnostic Ultrasound Using a Reference Phantom Method

Task-Oriented Comparison of Power Spectral Density Estimation Methods for Quantifying Acoustic Attenuation in Diagnostic Ultrasound Using a Reference Phantom Method

A New Subsample Time Delay Estimation Algorithm for LFM-Based Detection

Evaluation method of the degree of red blood cell aggregation considering ultrasonic propagation attenuation by analyzing ultrasonic backscattering properties

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