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Related Concept Videos

Blood Flow01:29

Blood Flow

Blood is pumped by the heart into the aorta, the largest artery in the body, and then into increasingly smaller arteries, arterioles, and capillaries. The velocity of blood flow decreases with increased cross-sectional blood vessel area. As blood returns to the heart through venules and veins, its velocity increases. The movement of blood is encouraged by smooth muscle in the vessel walls, the movement of skeletal muscle surrounding the vessels, and one-way valves that prevent backflow.
Flow Cytometry01:23

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...

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Related Experiment Video

Updated: May 7, 2026

Fluorescent Dye Labeling of Erythrocytes and Leukocytes for Studying the Flow Dynamics in Mouse Retinal Circulation
08:05

Fluorescent Dye Labeling of Erythrocytes and Leukocytes for Studying the Flow Dynamics in Mouse Retinal Circulation

Published on: July 3, 2017

Red blood cell tracking using optical flow methods.

Dongmin Guo, Anne L van de Ven, Xiaobo Zhou

    IEEE Journal of Biomedical and Health Informatics
    |September 24, 2013
    PubMed
    Summary
    This summary is machine-generated.

    Tracking red blood cells (RBCs) is vital for microcirculation research. New optical flow methods improve in vivo RBC tracking, even with unstable velocities and complex conditions, aiding disease therapy development.

    More Related Videos

    Doppler Optical Coherence Tomography of Retinal Circulation
    10:46

    Doppler Optical Coherence Tomography of Retinal Circulation

    Published on: September 18, 2012

    Related Experiment Videos

    Last Updated: May 7, 2026

    Fluorescent Dye Labeling of Erythrocytes and Leukocytes for Studying the Flow Dynamics in Mouse Retinal Circulation
    08:05

    Fluorescent Dye Labeling of Erythrocytes and Leukocytes for Studying the Flow Dynamics in Mouse Retinal Circulation

    Published on: July 3, 2017

    Doppler Optical Coherence Tomography of Retinal Circulation
    10:46

    Doppler Optical Coherence Tomography of Retinal Circulation

    Published on: September 18, 2012

    Area of Science:

    • Biomedical Engineering
    • Physiology
    • Medical Imaging

    Background:

    • Microcirculation research is crucial for monitoring health and developing disease therapies.
    • Red blood cell (RBC) tracking is key for estimating microcirculation parameters.
    • Existing spatiotemporal image analysis methods for RBC tracking face challenges with in vivo imaging, including unstable cell velocities and complex vessel structures.

    Purpose of the Study:

    • To develop robust methods for tracking red blood cells (RBCs) in microcirculation.
    • To address limitations of traditional RBC tracking techniques in challenging in vivo conditions.
    • To enable more accurate estimation of blood flow and other microcirculatory parameters.

    Main Methods:

    • Proposed an optical flow method to track RBCs by analyzing local motion and displacement between image frames.
    • Utilized scale-invariant feature transform (SIFT) flow as an alternative optical flow-based approach.
    • Applied methods to in vivo cell tracking scenarios with potential for spatial and temporal distortions.

    Main Results:

    • The proposed optical flow method demonstrated robustness to unstable RBC velocities.
    • SIFT flow proved effective for tracking cells with large displacements between frames.
    • Both optical flow methods outperformed existing techniques in in vivo RBC tracking.

    Conclusions:

    • Optical flow-based methods offer significant improvements for in vivo RBC tracking.
    • These advanced tracking techniques can directly estimate blood flow and aid in evaluating other microcirculatory parameters.
    • The developed methods contribute to better understanding and treatment of diseases affecting microcirculation.