Dataset for "Ultrasound Imaging Velocimetry with interleaved images for improved pulsatile arterial flow measurements: a new correction method, experimental and in vivo validation"

  • KH Fraser (Creator)
  • C. Poelma (Creator)
  • Z. Zhou (Creator)
  • E. Bazigou (Creator)
  • MX Tang (Creator)
  • PD Weinberg (Creator)

Dataset

Description

Blood velocity measurements are important in physiological science and clinical diagnosis. Doppler ultrasound is the most commonly used method but can only measure one velocity component. Ultrasound imaging velocimetry (UIV) is a promising technique capable of measuring two velocity components; however, there is a limit on the maximum velocity that can be measured with conventional hardware which results from the way images are acquired by sweeping the ultrasound beam across the field of view. Interleaved UIV is an extension of UIV in which two image frames are acquired concurrently, allowing the effective inter-frame separation time to be reduced and therefore increasing the maximum velocity that can be measured. The sweeping of the ultrasound beam across the image results in a systematic error which must be corrected: in this work we derived and implemented a new velocity correction method which accounts for acceleration of the scatterers. We then, for the first time, assessed the performance of interleaved UIV for measuring pulsatile arterial velocities by measuring flows in phantoms and in vivo and comparing the results with spectral Doppler ultrasound and transit-time flow probe data. The velocity and flow rate in the phantom agreed within 5-10 % of peak velocity, and 2-9% of peak flow, respectively and in vivo the velocity difference was 9 % of peak velocity. The maximum velocity measured was 1.8 m/s, the highest velocity reported with UIV. This will allow flows in diseased arteries to be investigated and so has the potential to increase diagnostic accuracy and enable new vascular research
Date made available2 Jan 2016
PublisherUniversity of Bath
Date of data production2016

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