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Ingvild Kinn Ekroll

Researcher at Norwegian University of Science and Technology

Publications -  42
Citations -  666

Ingvild Kinn Ekroll is an academic researcher from Norwegian University of Science and Technology. The author has contributed to research in topics: Doppler effect & Acoustic Doppler velocimetry. The author has an hindex of 10, co-authored 41 publications receiving 558 citations.

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Coherent Plane Wave Compounding for Very High Frame Rate Ultrasonography of Rapidly Moving Targets

TL;DR: A motion compensation technique based on cross-correlation was introduced, which significantly recovered the losses in SNR and contrast for physiological tissue velocities and the effects of motion were demonstrated in vivo when imaging a rat heart.
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Simultaneous quantification of flow and tissue velocities based on multi-angle plane wave imaging

TL;DR: Using the high ensemble vector Doppler technique, blood flow through stenoses and secondary flow patterns were better visualized than in ordinary color doppler, and the full velocity spectrum could be obtained retrospectively for arbitrary points in the image.
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Robust angle-independent blood velocity estimation based on dual-angle plane wave imaging

TL;DR: In vivo results indicated that a more robust angle-independent blood velocity estimator is obtained using compounded speckle tracking compared with conventional ST and VD methods.
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Coherent compounding in doppler imaging

TL;DR: It is shown that the bias in the mean velocity increases with increasing beam-to-flow angle and/or blood velocity, whereas the SNR decreases, and a 2-D motion correction scheme is proposed based on multi-angle vector Doppler velocity estimates, resulting in significantly reduced mean velocity bias and an SNR less dependent on blood velocity and direction.
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Combined Vector Velocity and Spectral Doppler Imaging for Improved Imaging of Complex Blood Flow in the Carotid Arteries

TL;DR: It was demonstrated that the combined information can be used to generate spatial maps of the peak systolic velocity, highlighting regions of high velocity and the extent of the stenotic region, which could be use to automate work flow as well as improve the accuracy of measurement of true peak syStolic velocity.