ArticleApplied optics2019
Velocimetry based on dye visualization for a pulsatile tubing flow measurement.
Article in Applied optics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The trial behind it
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Who cites it
1 citing paper in PubMed.
- Machine Learning for Aiding Blood Flow Velocity Estimation Based on Angiography.Bioengineering (Basel, Switzerland) · 2022Article
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Authors and funding
2 authors.
Funding
Abstract
A dye visualization experiment was designed and operated as an analogy of x-ray angiographic imaging. The velocimetry technique based on dye visualization for a pulsatile tubing flow measurement is introduced. The optical flow method was utilized to recover the velocity field from the visualization images. For the same flow condition, a digital particle image velocimetry (PIV) system was also employed to measure the same flow field in the middle plane. The purpose of this study was to determine the accuracy of the velocity field estimation from the transmittance-based two-dimensional projection image of the three-dimensional volumetric flow field by dye visualization in comparison with the PIV measurement results. Compared to the PIV results in the middle plane, the averaged velocity magnitude from the dye visualization measurement was underestimated by about 16%-24% in the central region and by about 29%-43% in the outer region across the tube at two time instants of the cyclic pulsatile flow.
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Registered trials
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