Vector velocity estimation for portable ultrasound using directional transverse oscillation and synthetic aperture sequential beamforming

In this paper, a vector flow imaging method is presented, which combines the directional transverse oscillation approach with synthetic aperture sequential beamforming to achieve an efficient estimation of the velocities. A double-oscillating field is synthesized using two sets of focused emissions separated by a distance in the lateral direction. A low-resolution line (LRL) is created for each emission in the first stage beamformer, and a second beamformer provides the high-resolution data used for the velocity estimation. The method makes it possible to have continuously available data in the whole image. Therefore, high and low velocities can be estimated with a high frame rate and a low standard deviation. The first stage is a fixed-focus beamformer that can be integrated in the transducer handle, enabling the wireless transmission of the LRLs. The approach does not require any angle compensation or prior knowledge on the beam-to-flow angle. The feasibility of the method is demonstrated through simulations and flow rig measurements of a parabolic flow in a vessel at 90-degree beam-to-flow angle. The mean bias obtained from 50 independent measurements is equal to -0.67% for the lateral profile and -0.43% for the axial profile. The relative standard deviation is 3.19% and 0.47% for the lateral and axial profiles. It is, therefore, demonstrated that vector velocity estimation can be efficiently integrated in a portable ultrasound scanner with state-of-the-art performance.

[1]  M. Fox Multiple crossed-beam ultrasound Doppler velocimetry , 1978 .

[2]  J. Jensen,et al.  Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers , 1992, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[3]  J. Jensen,et al.  A new method for estimation of velocity vectors , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[4]  Martin Christian Hemmsen,et al.  Implementation of real-time duplex synthetic aperture ultrasonography , 2015, 2015 IEEE International Ultrasonics Symposium (IUS).

[5]  M.E. Aderson,et al.  Multi-dimensional velocity estimation with ultrasound using spatial quadrature , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[6]  K. Boone,et al.  Effect of skin impedance on image quality and variability in electrical impedance tomography: a model study , 1996, Medical and Biological Engineering and Computing.

[7]  J. Jensen Improved vector velocity estimation using Directional Transverse Oscillation , 2015, 2015 IEEE International Ultrasonics Symposium (IUS).

[8]  Jørgen Arendt Jensen,et al.  Sequential beamforming for synthetic aperture imaging. , 2013, Ultrasonics.

[9]  S. Nikolov,et al.  Directional synthetic aperture flow imaging , 2004, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[10]  Jørgen Arendt Jensen,et al.  An object-oriented multi-threaded software beamformation toolbox , 2011, Medical Imaging.

[11]  G. Trahey,et al.  Angle Independent Ultrasonic Detection of Blood Flow , 1987, IEEE Transactions on Biomedical Engineering.

[12]  Kristoffer Lindskov Hansen,et al.  In vivo evaluation of synthetic aperture sequential beamforming. , 2012, Ultrasound in medicine & biology.

[13]  J A Jensen,et al.  A new estimator for vector velocity estimation. , 2001, IEEE transactions on ultrasonics, ferroelectrics, and frequency control.

[14]  J. Jensen,et al.  A new estimator for vector velocity estimation [medical ultrasonics] , 2001, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[15]  S. I. Nikolov,et al.  SARUS: A synthetic aperture real-time ultrasound system , 2013, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[16]  J. Arendt Paper presented at the 10th Nordic-Baltic Conference on Biomedical Imaging: Field: A Program for Simulating Ultrasound Systems , 1996 .