Estimation and display for Vector Doppler Imaging using planewave transmissions

Flynn, John A.; Daigle, Ron; Pflugrath, Lauren; Linkhart, Ken; Kaczkowski, Peter J.

doi:10.1109/ultsym.2011.0099

Cited by 23 publications

(14 citation statements)

References 4 publications

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“…Compared to the multi-angle planewave algorithm presented in [2], this approach allows for a longer time interval for wall filtering, as the frame is not partitioned into separate segments for different planewave angles. Longer wall filter impulse responses with steeper transition bands are then possible, for equivalent capture window times.…”

Section: A Statement Of Contribution/methodsmentioning

confidence: 99%

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High framerate vector velocity blood flow imaging using a single planewave transmission angle

Flynn¹,

Daigle²,

Pflugrath³

et al. 2012

2012 IEEE International Ultrasonics Symposium

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Vector velocity blood flow imaging gives speed and direction of blood flow at each pixel. An imaging algorithm proposed earlier [2] requires multiple angles of planewave (PW) transmissions to construct a robustly invertible model for vector velocity estimates.Here we demonstrate a vector velocity estimation approach that requires only a single planewave transmission angle. The proposed algorithm uses PW transmission and reconstruction to generate a blood motion image sequence in the B-mode flow (B-Flow) modality, at frame rates in the Doppler PRF regime. Pixel ensembles in the image sequence at point p = [x, z] and pulse t are comprised of IQ magnitude values, computed from the IQ data at each pixel p after wall filtering the ensemble. The sequence of values thus captures motion at a framerate equal to the PRF, revealing fine-scale flow dynamics as a moving texture in the blood reflectivity.Using the chain rule, spatial and temporal derivatives resulting from the space-time gradient of the image sequence couple to the texture flow velocity vector field [vx(x, z, t), vz(x, z, t)] at each pixel p and PRI t. The resulting Gauss-Markov models are solved by least squares to give the vector velocity estimates, which are formulated in the model to be constant over the estimation window.We also evaluate variants that include in the observation, lagproduct samples (autocorrelation summands) at non-zero lags, as well as instantaneous Doppler-derived axial velocity estimates.Compared to the multi-angle planewave algorithm presented in [2], this approach allows for a longer time interval for wall filtering, as the frame is not partitioned into separate segments for different planewave angles. This permits wall filters with steeper transition bands, and allows flexibility in balancing framerate and sensitivity, suggesting application to vector flow imaging of deep tissue where efficiently achieving planewave angle diversity at the target becomes difficult.Using a Philips L7-4 transducer and a Verasonics (TM) acquisition system, we evaluate single-angle PWT vector velocity imaging on a Doppler string phantom, and demonstrate it successfully on a carotid artery.

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Section: A Statement Of Contribution/methodsmentioning

confidence: 99%

“…An imaging algorithm proposed earlier [2] requires multiple angles of planewave (PW) transmissions to construct a robustly invertible model for vector velocity estimates.…”

Section: Introductionmentioning

confidence: 99%

High framerate vector velocity blood flow imaging using a single planewave transmission angle

Flynn¹,

Daigle²,

Pflugrath³

et al. 2012

2012 IEEE International Ultrasonics Symposium

Self Cite

View full text Add to dashboard Cite

show abstract

“…The common attribute of these visualization schemes is that the flow vectors are shown on a static basis in which they are always pivoted at the same pixel position. To more lucidly highlight the dynamic nature of blood flow, especially in cases with complex flow patterns, efforts have been made to dynamically update the position of flow vectors in between frames by applying particle visualization strategies that are well established in computer vision [147], [148], [149].…”

Section: Dynamic Visualizationmentioning

confidence: 99%

Ultrasound Vector Flow Imaging: I: Sequential Systems

Jensen

Nikolov²,

et al. 2016

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

107

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Abstract-The paper gives a review of the most important methods for blood velocity vector flow imaging (VFI) for conventional, sequential data acquisition. This includes multibeam methods, speckle tracking, transverse oscillation, color flow mapping derived vector flow imaging, directional beamforming, and variants of these. The review covers both 2-D and 3-D velocity estimation and gives a historical perspective on the development along with a summary of various vector flow visualization algorithms. The current state-of-the-art is explained along with an overview of clinical studies conducted and methods for presenting and using VFI. A number of examples of VFI images are presented, and the current limitations and potential solutions are discussed.

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“…These newer schemes have appeared in the forms of: (i) single-line, multi-gate flow vector estimation [71], [72], and (ii) flow vector mapping over the entire field of view [73], [74], [75]. One key feature that is shared among these new formulations is the use of plane wave excitation schemes for transmission [76], [77], so as to enhance the frame rate as described earlier in this article. It is worth noting that highframe-rate, least-squares flow vector estimation technology [78] will become clinically available as a real-time, highframe-rate diagnostic mode as part of Mindray's new Resona 7 platform in 2016.…”

Section: Multi-direction Velocity Estimationmentioning

confidence: 99%

Ultrasound Vector Flow Imaging—Part II: Parallel Systems

Jensen

Nikolov

et al. 2016

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Abstract-The paper gives a review of the current state-of-theart in ultrasound parallel acquisition systems for flow imaging using spherical and plane waves emissions. The imaging methods are explained along with the advantages of using these very fast and sensitive velocity estimators. These experimental systems are capable of acquiring thousands of images per second for fast moving flow as well as yielding estimates of low velocity flow. These emerging techniques allow vector flow systems to assess highly complex flow with transitory vortices and moving tissue, and they can also be used in functional ultrasound imaging for studying brain function in animals. The paper explains the underlying acquisition and estimation methods for fast 2-D and 3-D velocity imaging and gives a number of examples. Future challenges and the potentials of parallel acquisition systems for flow imaging are also discussed.

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Estimation and display for Vector Doppler Imaging using planewave transmissions

Cited by 23 publications

References 4 publications

High framerate vector velocity blood flow imaging using a single planewave transmission angle

High framerate vector velocity blood flow imaging using a single planewave transmission angle

Ultrasound Vector Flow Imaging: I: Sequential Systems

Ultrasound Vector Flow Imaging—Part II: Parallel Systems

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