Nonstationarity broadening in pulsed doppler spectrum measurements

Fish, P.J.

doi:10.1016/0301-5629(91)90122-d

Cited by 63 publications

(30 citation statements)

References 4 publications

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“…This measure potentially allows the correction for spectral broadening [10,12,13,15]. The continuous wavelet transform (CWT) can be expressed in a time-frequency version as [6]:…”

Section: Doppler Spectral Widthmentioning

confidence: 99%

“…The models conclude that the Doppler signal from undisturbed flow is random, with a Gaussian probability density function and a spectral width determined by the range of magnitudes of the velocities of the streamlines passing through the sample volume and by the sample volume characteristics. Due to the pulsatile nature of the blood flow, the Doppler signal x(t) windowed by w(t) is not stationary, it can be written as [10]:…”

Section: Doppler Spectral Widthmentioning

confidence: 99%

“…On the other hand, we can also obtain the rms width of |W 1 s (f, t)| 2 by numerical calculations [10,13].…”

Section: Broadening Correctionmentioning

confidence: 99%

“…When using the STFT, there is an obvious tradeoff between the poor spectral resolution introduced by short data windows and the spectral broadening that arises from nonstationary characteristics of the signal when using longer data windows. Much progress has been made in identifying and quantifying spectral broadening resulting from blood flow nonstationarity [10][11][12]. In this broadening error, the effects of window duration broadening and nonstationarity broadening based on the STFT with different windows and rates of change of mean frequency can be separately identified [10].…”

Section: Introductionmentioning

confidence: 99%

“…Much progress has been made in identifying and quantifying spectral broadening resulting from blood flow nonstationarity [10][11][12]. In this broadening error, the effects of window duration broadening and nonstationarity broadening based on the STFT with different windows and rates of change of mean frequency can be separately identified [10]. The nonstationarity and window broadening in Doppler spectrum estimation based on the STFT using Hanning windows and Gaussian windows have been calculated and the spectral width estimation has been corrected [13].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Correction for broadening in Doppler blood flow spectrum estimated using wavelet transform

Zhang

Chen

et al. 2006

Medical Engineering & Physics

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“…This measure potentially allows the correction for spectral broadening [10,12,13,15]. The continuous wavelet transform (CWT) can be expressed in a time-frequency version as [6]:…”

Section: Doppler Spectral Widthmentioning

confidence: 99%

Section: Doppler Spectral Widthmentioning

confidence: 99%

“…On the other hand, we can also obtain the rms width of |W 1 s (f, t)| 2 by numerical calculations [10,13].…”

Section: Broadening Correctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Correction for broadening in Doppler blood flow spectrum estimated using wavelet transform

Zhang

Chen

et al. 2006

Medical Engineering & Physics

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Design and Construction of a Blood Flow Detector Probe for Medical Application

et al. 2004

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Developments in cardiovascular ultrasound: Part 1: Signal processing and instrumentation

Fish

Hoskins

Moran

et al. 1997

Med. Biol. Eng. Comput.

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One of the major contributions to the improvement of spectral Doppler and colour flow imaging instruments has been the development of advanced signal-processing techniques made possible by increasing computing power. Model-based or parametric spectral estimators, time-frequency transforms, station-arising algorithms and spectral width correction techniques have been investigated as possible improvements on the FFT-based estimators currently used for real-time spectral estimation of Doppler signals. In colour flow imaging some improvement on velocity estimation accuracy has been achieved by the use of new algorithms but at the expense of increased computational complexity compared with the conventional autocorrelation method. Polynomial filters have been demonstrated to have some advantages over IIR filters for stationary echo cancellation. Several methods of velocity vector estimation to overcome the problem of angle dependence have been studied, including 2D feature tracking, two and three beam approaches and the use of spectral width in addition to mean frequency. 3D data acquisition and display and Doppler power imaging have also been investigated. The use of harmonic imaging, using the second harmonic generated by encapsulated bubble contrast media, seems promising particularly for imaging slow flow. Parallel image data acquisition using non-sequential scanning or broad beam transmission, followed by simultaneous reception along a number of beams, has been studied to speed up 'real-time' imaging.

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Nonstationarity broadening in pulsed doppler spectrum measurements

Cited by 63 publications

References 4 publications

Correction for broadening in Doppler blood flow spectrum estimated using wavelet transform

Correction for broadening in Doppler blood flow spectrum estimated using wavelet transform

Design and Construction of a Blood Flow Detector Probe for Medical Application

Developments in cardiovascular ultrasound: Part 1: Signal processing and instrumentation

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