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particle image velocimetry algorithm  (MathWorks Inc)


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    MathWorks Inc particle image velocimetry algorithm
    Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
    Particle Image Velocimetry Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2900 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/particle+image+velocimetry+algorithm/Image+Processing+Toolbox/10__1002_slash_aisy__202300465-201-13-19
    Average 96 stars, based on 2900 article reviews
    particle image velocimetry algorithm - by Bioz Stars, 2026-09
    96/100 stars

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    1) Product Images from "Acoustically Actuated Flow in Microrobots Powered by Axisymmetric Resonant Bubbles"

    Article Title: Acoustically Actuated Flow in Microrobots Powered by Axisymmetric Resonant Bubbles

    Journal: Advanced Intelligent Systems

    doi: 10.1002/aisy.202300465

    Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image velocimetry algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
    Figure Legend Snippet: Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image velocimetry algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.

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    other:

    Article Title: Acoustically Actuated Flow in Microrobots Powered by Axisymmetric Resonant Bubbles
    Article Snippet: Moreover, the microrobot ejects the debris through its inner channel away from the substrate as this can be seen from the out-of-focus Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image velocimetry algorithm (PIVlab, MATLAB).

    Article Title: Acoustically Actuated Flow in Microrobots Powered by Axisymmetric Resonant Bubbles
    Article Snippet: We analyze the flow velocity at the inlet side (Figure 5a) using the particle image velocimetry algorithm (PIVlab toolbox, MATLAB)[38] and determine the peak velocity by analyzing the particle velocity along the sectional line perpendicular to the flow direction (Figure 5b, Movie S3, Supporting Information).

    Article Title: Self-Driven Jamming in Growing Microbial Populations
    Article Snippet: We measure the cell outflow rate Jcell from time lapse movies using a custom-made particle image velocimetry algorithm (Matlab), and infer the growth rate in the chamber as k = Jcell/Vch, where Vch is the volume of the growth chamber.

    Article Title: Polar actomyosin contractility destabilizes the position of the cytokinetic furrow.
    Article Snippet: Cytokinesis, the physical separation of daughter cells at the end of mitosis, requires precise regulation of the mechanical properties of the cell periphery.. Although studies of cytokinetic mechanics mostly focus on the equatorial constriction ring, a contractile actomyosin cortex is also present at the poles of dividing cells.. Whether polar forces influence cytokinetic cell shape and furrow positioning remains an open question.



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    Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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    Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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    Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image <t>velocimetry</t> algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.
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    Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image velocimetry algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.

    Journal: Advanced Intelligent Systems

    Article Title: Acoustically Actuated Flow in Microrobots Powered by Axisymmetric Resonant Bubbles

    doi: 10.1002/aisy.202300465

    Figure Lengend Snippet: Figure 5. a) Superimposed time-lapse images showing the acoustic streaming pattern around microrobots with 6 and 18 oscillating microbubbles. b) Computation of the flow analysis using particle image velocimetry algorithm (PIVlab, MATLAB).[38] A sectional line A–A 0 is selected at the inlet side of the microrobot to analyze the flow velocity magnitude profile of a selected frame. c) The flow velocity magnitude profile along the line A–A 0. In the n = 6 case, the maximal flow velocity is 0.99 mm s1, whereas in the n = 18 case, the maximal flow velocity is 1.77 mm s1. This result shows that the acoustic streaming intensity can be strengthened in multibubble systems with a larger number of simultaneously oscillating bubbles. The x-axis from left to right corresponds to the section line from top to bottom in (b). Scale bars are 500 μm.

    Article Snippet: We analyze the flow velocity at the inlet side (Figure 5a) using the particle image velocimetry algorithm (PIVlab toolbox, MATLAB)[38] and determine the peak velocity by analyzing the particle velocity along the sectional line perpendicular to the flow direction (Figure 5b, Movie S3, Supporting Information).

    Techniques: