An axial velocity estimator for ultrasound blood flow imaging, based on a full evaluation of the Doppler equation by means of a two-dimensional autocorrelation approach

Loupas, T.; Powers, Jeffrey; Gill, R.W.

doi:10.1109/58.393110

Cited by 463 publications

(288 citation statements)

References 39 publications

Supporting

Mentioning

281

Contrasting

Order By: Relevance

“…The analytic versions of the post-beamformed RF US signals were first calculated using the Hilbert transform. From the analytic signals, tissue displacement was calculated using the 2-D autocorrelation estimator (Loupas et al 1995), which estimates the mean change in phase of the quadrature-demodulated or analytic signal in slow-time, i.e., pulse-to-pulse, as well as fast-time, i.e., depth-to-depth. If multiple scan lines are included in the calculation, the displacement for a particular sample volume can be written as:…”

Section: Discussionmentioning

confidence: 99%

Tissue Pulsatility Imaging of Cerebral Vasoreactivity During Hyperventilation

Kucewicz

Dunmire

Giardino

et al. 2008

Ultrasound in Medicine & Biology

View full text Add to dashboard Cite

Tissue Pulsatility Imaging (TPI) is an ultrasonic technique that is being developed at the University of Washington to measure tissue displacement or strain due to blood flow over the cardiac and respiratory cycles. This technique is based in principle on plethysmography, an older non-ultrasound technology for measuring expansion of a whole limb or body part due to perfusion. TPI adapts tissue Doppler signal processing methods to measure the "plethysmographic" signal from hundreds or thousands of sample volumes in an ultrasound image plane. This paper presents a feasibility study to determine if TPI can be used to assess cerebral vasoreactivity. Ultrasound data were collected transcranially through the temporal acoustic window from four subjects before, during, and after voluntary hyperventilation. In each subject, decreases in tissue pulsatility during hyperventilation were observed that were statistically correlated with the subject's end-tidal CO 2 measurements.

show abstract

Section: Discussionmentioning

confidence: 99%

Tissue Pulsatility Imaging of Cerebral Vasoreactivity During Hyperventilation

Kucewicz

Dunmire

Giardino

et al. 2008

Ultrasound in Medicine & Biology

View full text Add to dashboard Cite

show abstract

“…The analytic versions of the post-beamformed RF US signals were first calculated using the Hilbert transform. From the analytic signals, tissue displacement was measured using the 2D autocorrelation estimator (Loupas et al 1995). The standard 1D autocorrelator estimates the mean change in phase of the quadrature demodulated or analytic signal in slow-time, i.e.…”

Section: Displacement Estimationmentioning

confidence: 99%

Functional Tissue Pulsatility Imaging of the Brain During Visual Stimulation

Kucewicz

Dunmire

Leotta

et al. 2007

Ultrasound in Medicine & Biology

View full text Add to dashboard Cite

Functional tissue pulsatility imaging (fTPI) is a new ultrasonic technique being developed to map brain function by measuring changes in tissue pulsatility due to changes in blood flow with neuronal activation. The technique is based in principle on plethysmography, an older, non-ultrasound technology for measuring expansion of a whole limb or body part due to perfusion. Perfused tissue expands by a fraction of a percent early in each cardiac cycle when arterial inflow exceeds venous outflow and relaxes later in the cardiac cycle when venous drainage dominates. Tissue pulsatility imaging (TPI) uses tissue Doppler signal processing methods to measure this pulsatile "plethysmographic" signal from hundreds or thousands of sample volumes in an ultrasound image plane. A feasibility study was conducted to determine if TPI could be used to detect regional brain activation during a visual contrast-reversing checkerboard block paradigm study. During a study, ultrasound data were collected transcranially from the occipital lobe as a subject viewed alternating blocks of a reversing checkerboard (stimulus condition) and a static, gray screen (control condition). Multivariate Analysis of Variance (MANOVA) was used to identify sample volumes with significantly different pulsatility waveforms during the control and stimulus blocks. In 7 out 14 studies, consistent regions of activation were detected from tissue around the major vessels perfusing the visual cortex.

show abstract

“…In Fig. 3(b), the center frequency estimation proposed in [2] was used together with the conventional method [1]. However, the strain estimates are not improved so much.…”

Section: Basic Experimental Resultsmentioning

confidence: 99%

“…Under such a condition, the displacement estimates are biased because it is obtained using the phase changes and center frequencies of received RF echoes. An autocorrelation-based method was proposed to compensate for this apparent change in center frequency [2,3]. In this method, center frequency distributions in two frames must be assumed to be the same.…”

mentioning

confidence: 99%

Strain Imaging of Arterial Wall with Reduction of Effects of Variation in Center Frequency of Ultrasonic RF Echo

Hasegawa

Kanai

2009

IFMBE Proceedings

View full text Add to dashboard Cite

Abstract-Atherosclerotic change of the arterial wall leads to a significant change in its elasticity. For assessment of elasticity, measurement of arterial wall deformation is required. For motion estimation, correlation techniques are widely used, and we developed a phase-sensitive correlation method, namely, the phased-tracking method, to measure the regional strain of the arterial wall due to the heartbeat. Although phasesensitive methods using demodulated complex signals require less computation in comparison with methods using the correlation between RF signals or iterative methods, the displacement estimated by such phase-sensitive methods are biased when the center frequency of the RF echo apparently varies. One of the reasons for the apparent change in the center frequency would be the interference of echoes from scatterers within the wall. In the present study, a method was introduced to reduce the influence of variation in the center frequencies of RF echoes on the estimation of the artery-wall strain when using the phase-sensitive correlation technique. The improvement in the strain estimation by the proposed method was validated using a phantom. The error from the theoretical strain profile and the standard deviation in strain estimated by the proposed method were 12.0% and 14.1%, respectively, significantly smaller than those (23.7% and 46.2%) obtained by the conventional phase-sensitive correlation method. Furthermore, in the preliminary in vitro experimental results, the strain distribution of the arterial wall well corresponded with pathology, i.e., the region with calcified tissue showed very small strain, and the region almost homogeneously composed of smooth muscle and collagen showed relatively larger strain and clear strain decay with respect to the radial distance from the lumen.

show abstract

An axial velocity estimator for ultrasound blood flow imaging, based on a full evaluation of the Doppler equation by means of a two-dimensional autocorrelation approach

Cited by 463 publications

References 39 publications

Tissue Pulsatility Imaging of Cerebral Vasoreactivity During Hyperventilation

Tissue Pulsatility Imaging of Cerebral Vasoreactivity During Hyperventilation

Functional Tissue Pulsatility Imaging of the Brain During Visual Stimulation

Strain Imaging of Arterial Wall with Reduction of Effects of Variation in Center Frequency of Ultrasonic RF Echo

Contact Info

Product

Resources

About