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ABSTRACT: Wilson (1991) presented an ultrasonic wideband estimator for axial blood flow velocity estimation through the use of the 2-D Fourier transform. It was shown how a single velocity component was concentrated along a line in the 2-D Fourier space, where the slope was given by the axial velocity. Later, it was shown that this approach could also be used for finding the lateral velocity component by also including a lateral sampling. A single velocity component would then be concentrated along a plane in the 3-D Fourier space, tilted according to the 2 velocity components. This paper presents 2 new velocity estimators for finding both the axial and lateral velocity components. The estimators essentially search for the plane in the 3- D Fourier space, where the integrated power spectrum is largest. The first uses the 3-D Fourier transform to find the power spectrum, while the second uses a minimum variance approach. Based on this plane, the axial and lateral velocity components are estimated. Several phantom measurements, for flow-to-depth angles of 60, 75, and 90 degrees, were performed. Multiple parallel lines were beamformed simultaneously, and 2 different receive apodization schemes were tried. The 2 estimators were then applied to the data. The axial velocity component was estimated with an average standard deviation below 2.8% of the peak velocity, while the average standard deviation of the lateral velocity estimates was between 2.0% and 16.4%. The 2 estimators were also tested on in vivo data from a transverse scan of the common carotid artery, showing the potential of the vector velocity estimation method under in vivo conditions.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control 09/2008; 55(8):1744-54. · 1.80 Impact Factor
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ABSTRACT: Ultrasonic color flow maps are made by estimating the velocities line by line over the region of interest. For each velocity estimate, multiple repetitions are needed. This sets a limit on the frame rate, which becomes increasingly severe when imaging deeper lying structures or when simultaneously acquiring spectrogram data for triplex imaging. This paper proposes a method for decreasing the data acquisition time by simultaneously sampling multiple lines for color flow maps, using narrow band signals with approximately disjoint spectral support. The signals are separated in the receiver by filters matched to the emitted waveforms, producing a number of data sets with different center frequencies. The autocorrelation estimator is then applied to each of the data sets. The method is presented, various side effects are considered, and the method is tested on data from a recirculating flow phantom. A mean standard deviation across the flow profile of 3.1, 2.5, and 2.1% of the peak velocity was found for bands at 5 MHz, 7 MHz, and 9 MHz, respectively. Alternatively, the method can be used for simultaneously sampling data for a color flow map and for multiple spectrograms using different spectral bands. Using three spectral bands, data for a color flow map and two independent spectrograms can be acquired at the time normally spent on acquiring data for a color flow map only. This yields an expansion of triplex imaging called multifrequency quadroplex imaging, which enables study of the flow over an arterial stenosis by simultaneously acquiring spectrograms on both sides of the stenosis, while maintaining the color flow map. The method was tested in vivo on data from the common carotid artery of a healthy male volunteer, both for fast color flow mapping and for multifrequency quadroplex imaging.
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control 05/2008; 55(4):778-86. · 1.69 Impact Factor
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ABSTRACT: Previously, a synthetic aperture vector velocity estimation method was proposed. Data are beamformed at different directions through a point, where the velocity is estimated. The flow direction is estimated by a search for the direction where the normalized cross-correlation peaks and the velocity magnitude along this direction are found. In this paper, different effects that influence the focusing in this method are investigated. These include the effect of phase errors in the emitted spherical waves, motion effects, and the effect of various interpolation methods in beam-forming. A model based on amplitude drop and phase error for spherical waves created using the virtual source concept is derived. This model can be used to determine the opening angle of a virtual source. Simulations for different virtual source placements are made, and it is recommended that the virtual sources be placed behind the aperture when shallow structures are imaged, and when deeper-lying structures are imaged the virtual sources be placed in front of the aperture. Synthetic aperture methods involve summation of data from numerous emissions. Motion between these emissions results in incoherence and affects resolution, contrast, and the signal-to-noise ratio. The effects of motion on the synthetic aperture vector velocity estimation method are investigated, and it is shown that for both axial and lateral motion, the contrast and signal-to-noise ratio can be seriously affected. A compensation method using the previous vector velocity estimate, when new data are beamformed, is implemented and tested. It is shown from a number of flow phantom experiments that a significant improvement with respect to bias and standard deviation of the velocity estimates can be obtained by using this compensation. Increased performance is gained at the expense of computation time. Different interpolation methods can be used for beam-forming the data. In this paper, the velocity estimation performance using various more complex interpolation schemes are compared to that using linear interpolation. No significant difference in the performance of the method is seen when other interpolation methods are used.
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control 10/2007; 54(9):1811-25. · 1.69 Impact Factor
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ABSTRACT: A method for determining both velocity magnitude and angle in a synthetic aperture ultrasound system is described. The approach uses directional beamforming along the flow direction and cross correlation to determine velocity magnitude. The angle of the flow is determined from the maximum normalized correlation calculated as a function of angle. This assumes the flow direction is within the imaging plane. Simulations of the angle estimation method show both biases and standard deviations of the flow angle estimates below 3 degrees for flow angles from 20 degrees to 90 degrees (transverse flow). The method is also investigated using data measured by an experimental ultrasound scanner from a flow rig. A commercial 128 element 7-MHz linear array transducer is used, and data are measured for flow angles of 60 degrees and 90 degrees . Data are acquired using the RASMUS experimental ultrasound scanner, which samples 64 channels simultaneously. A 20-micros chirp was used during emission and eight virtual transmit sources were created behind the transducer using 11 transmitting elements. Data from the eight transmissions are beamformed and coherently summed to create high-resolution lines at different angles for a set of points within the region of flow. The velocity magnitude is determined with a precision of 0.36% (60 degrees) and 1.2% (90 degrees), respectively. The 60 degrees angle is estimated with a bias of 0.54 degrees and a standard deviation of 2.1 degrees. For 90 degrees the bias is 0.0003 degrees and standard deviation 1.32 degrees. A parameter study with regard to correlation length and number of emissions is performed to reveal the accuracy of the method. Real time data covering 2.2 s of the carotid artery of a healthy 30-year-old male volunteer is acquired and then processed offline using a computer cluster. The direction of flow is estimated using the above mentioned method. It is compared to the flow angle of 106 degrees with respect to the axial direction, determined visually from the B-mode image. For a point in the center of the common carotid artery, 76% of the flow angle estimates over the 2.2 s were within 10 degrees of the visually determined flow angle. The standard deviation of these estimates was below 2.7 degrees. Full color flow maps from different parts of the cardiac cycle are presented, including vector arrows indicating both estimated flow direction and velocity magnitude.
IEEE Transactions on Medical Imaging 01/2007; 25(12):1637-44. · 3.64 Impact Factor
