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Deep learning and computer vision techniques for microcirculation analysis: A review.

Maged Helmy1, Trung Tuyen Truong2, Eric Jul1,3

  • 1Department of Informatics, University of Oslo, Oslo, Norway.

Patterns (New York, N.Y.)
|January 26, 2023
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Summary

Automating microcirculation image analysis using computer vision can aid in early disease detection. This survey guides researchers in developing systems for quantifying capillary density and distribution in critically ill patients.

Keywords:
image analysisliterature surveymicrocirculation analysis

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Critical Care Medicine

Background:

  • Microcirculation imaging analysis can detect early signs of critical illnesses like sepsis.
  • Quantifying capillary density and distribution serves as a vital biomarker for patient assessment.
  • Manual analysis is labor-intensive, time-consuming, and prone to interobserver variability.

Purpose of the Study:

  • To survey computer vision algorithms for automating microcirculation image analysis.
  • To identify promising techniques for quantifying capillary markers.
  • To provide a guide for developing automated microcirculation analysis systems.

Main Methods:

  • Comprehensive literature review of over 50 research papers.
  • Analysis and categorization of computer vision techniques applied to microcirculation imaging.
  • Evaluation of methods for automated quantification of capillary density and distribution.

Main Results:

  • Identification of the most relevant and promising computer vision algorithms.
  • Overview of current methods employed by researchers for automated analysis.
  • Highlighting the potential of automated systems to overcome manual analysis limitations.

Conclusions:

  • Computer vision offers a viable solution to automate labor-intensive microcirculation image analysis.
  • This survey serves as a crucial resource for researchers developing clinical diagnostic tools.
  • Automated analysis can improve the efficiency and reliability of biomarker quantification in critical care.