Literature DB >> 26452274

Automated Assessment of Hemodynamics in the Conjunctival Microvasculature Network.

Maziyar M Khansari, Justin Wanek, Anthony E Felder, Nicole Camardo, Mahnaz Shahidi.   

Abstract

The conjunctival microcirculation is accessible for direct visualization and quantitative assessment of microvascular hemodynamic properties. Currently available methods to assess hemodynamics in the conjunctival microvasculature use manual or semi-automated algorithms, which can be inefficient for application to a large number of microvessels within the microvascular network. We present an automated image analysis method for measurements of diameter and blood velocity in microvessels. The method was applied to conjunctival microcirculation images acquired in 15 healthy human subjects. Frangi filtering, thresholding, and morphological closing were applied to automatically segment microvessels, while variance filtering was used to detect blood flow. Diameter and blood velocity were measured in arterioles and venules within the conjunctival microvascular network, and blood flow and wall shear rate were calculated. Repeatability and validity of hemodynamic measurements were established. The automated image analysis method allows reliable, rapid and quantitative assessment of hemodynamics in the conjunctival microvascular network and can be potentially applied to microcirculation images of other tissues.

Entities:  

Mesh:

Year:  2015        PMID: 26452274      PMCID: PMC4821773          DOI: 10.1109/TMI.2015.2486619

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  27 in total

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4.  Assessment of Conjunctival Microvascular Hemodynamics in Stages of Diabetic Microvasculopathy.

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8.  Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm.

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