A computer vision approach for analyzing label free leukocyte trafficking dynamics on a microvascular mimetic Article Swipe
S. Danial Ahmad
,
Müjdat Çetin
,
Richard E. Waugh
,
James L. McGrath
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fimmu.2023.1140395
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fimmu.2023.1140395
High-content imaging techniques in conjunction with in vitro microphysiological systems (MPS) allow for novel explorations of physiological phenomena with a high degree of translational relevance due to the usage of human cell lines. MPS featuring ultrathin and nanoporous silicon nitride membranes (µSiM) have been utilized in the past to facilitate high magnification phase contrast microscopy recordings of leukocyte trafficking events in a living mimetic of the human vascular microenvironment. Notably, the imaging plane can be set directly at the endothelial interface in a µSiM device, resulting in a high-resolution capture of an endothelial cell (EC) and leukocyte coculture reacting to different stimulatory conditions. The abundance of data generated from recording observations at this interface can be used to elucidate disease mechanisms related to vascular barrier dysfunction, such as sepsis. The appearance of leukocytes in these recordings is dynamic, changing in character, location and time. Consequently, conventional image processing techniques are incapable of extracting the spatiotemporal profiles and bulk statistics of numerous leukocytes responding to a disease state, necessitating labor-intensive manual processing, a significant limitation of this approach. Here we describe a machine learning pipeline that uses a semantic segmentation algorithm and classification script that, in combination, is capable of automated and label-free leukocyte trafficking analysis in a coculture mimetic. The developed computational toolset has demonstrable parity with manually tabulated datasets when characterizing leukocyte spatiotemporal behavior, is computationally efficient and capable of managing large imaging datasets in a semi-automated manner.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fimmu.2023.1140395
- https://www.frontiersin.org/articles/10.3389/fimmu.2023.1140395/pdf
- OA Status
- gold
- Cited By
- 6
- References
- 66
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4360866232
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4360866232Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fimmu.2023.1140395Digital Object Identifier
- Title
-
A computer vision approach for analyzing label free leukocyte trafficking dynamics on a microvascular mimeticWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-03-24Full publication date if available
- Authors
-
S. Danial Ahmad, Müjdat Çetin, Richard E. Waugh, James L. McGrathList of authors in order
- Landing page
-
https://doi.org/10.3389/fimmu.2023.1140395Publisher landing page
- PDF URL
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https://www.frontiersin.org/articles/10.3389/fimmu.2023.1140395/pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/articles/10.3389/fimmu.2023.1140395/pdfDirect OA link when available
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Computer science, Pipeline (software), Segmentation, Interface (matter), Artificial intelligence, Computational biology, Biology, Programming language, Parallel computing, Maximum bubble pressure method, BubbleTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 4, 2023: 1Per-year citation counts (last 5 years)
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66Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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