Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition. / Kampen, Peter Johannes Tejlgaard; Støttrup-Als, Gustav Ragnar; Bruun-Andersen, Nicklas; Secher, Joachim; Høier, Freja; Hansen, Anne Todsen; Dziegiel, Morten Hanefeld; Christensen, Anders Nymark; Berg-Sørensen, Kirstine.

In: Biomedical Microdevices, Vol. 26, No. 1, 5, 2024.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Kampen, PJT, Støttrup-Als, GR, Bruun-Andersen, N, Secher, J, Høier, F, Hansen, AT, Dziegiel, MH, Christensen, AN & Berg-Sørensen, K 2024, 'Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition', Biomedical Microdevices, vol. 26, no. 1, 5. https://doi.org/10.1007/s10544-023-00688-6

APA

Kampen, P. J. T., Støttrup-Als, G. R., Bruun-Andersen, N., Secher, J., Høier, F., Hansen, A. T., Dziegiel, M. H., Christensen, A. N., & Berg-Sørensen, K. (2024). Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition. Biomedical Microdevices, 26(1), [5]. https://doi.org/10.1007/s10544-023-00688-6

Vancouver

Kampen PJT, Støttrup-Als GR, Bruun-Andersen N, Secher J, Høier F, Hansen AT et al. Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition. Biomedical Microdevices. 2024;26(1). 5. https://doi.org/10.1007/s10544-023-00688-6

Author

Kampen, Peter Johannes Tejlgaard ; Støttrup-Als, Gustav Ragnar ; Bruun-Andersen, Nicklas ; Secher, Joachim ; Høier, Freja ; Hansen, Anne Todsen ; Dziegiel, Morten Hanefeld ; Christensen, Anders Nymark ; Berg-Sørensen, Kirstine. / Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition. In: Biomedical Microdevices. 2024 ; Vol. 26, No. 1.

Bibtex

@article{0dc85e6517454b66850854b06a605210,

title = "Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition",

abstract = "Flow based deformation cytometry has shown potential for cell classification. We demonstrate the principle with an injection moulded microfluidic chip from which we capture videos of adult and fetal red blood cells, as they are being deformed in a microfluidic chip. Using a deep neural network - SlowFast - that takes the temporal behavior into account, we are able to discriminate between the cells with high accuracy. The accuracy was larger for adult blood cells than for fetal blood cells. However, no significant difference was observed between donors of the two types.",

keywords = "Deformation, Microfluidic flow cytometry, Neural network, Red blood cell, SlowFast",

author = "Kampen, {Peter Johannes Tejlgaard} and St{\o}ttrup-Als, {Gustav Ragnar} and Nicklas Bruun-Andersen and Joachim Secher and Freja H{\o}ier and Hansen, {Anne Todsen} and Dziegiel, {Morten Hanefeld} and Christensen, {Anders Nymark} and Kirstine Berg-S{\o}rensen",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2024",

doi = "10.1007/s10544-023-00688-6",

language = "English",

volume = "26",

journal = "Biomedical Microdevices",

issn = "1387-2176",

publisher = "Springer",

number = "1",

}

RIS

TY - JOUR

T1 - Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition

AU - Kampen, Peter Johannes Tejlgaard

AU - Støttrup-Als, Gustav Ragnar

AU - Bruun-Andersen, Nicklas

AU - Secher, Joachim

AU - Høier, Freja

AU - Hansen, Anne Todsen

AU - Dziegiel, Morten Hanefeld

AU - Christensen, Anders Nymark

AU - Berg-Sørensen, Kirstine

PY - 2024

Y1 - 2024

N2 - Flow based deformation cytometry has shown potential for cell classification. We demonstrate the principle with an injection moulded microfluidic chip from which we capture videos of adult and fetal red blood cells, as they are being deformed in a microfluidic chip. Using a deep neural network - SlowFast - that takes the temporal behavior into account, we are able to discriminate between the cells with high accuracy. The accuracy was larger for adult blood cells than for fetal blood cells. However, no significant difference was observed between donors of the two types.

AB - Flow based deformation cytometry has shown potential for cell classification. We demonstrate the principle with an injection moulded microfluidic chip from which we capture videos of adult and fetal red blood cells, as they are being deformed in a microfluidic chip. Using a deep neural network - SlowFast - that takes the temporal behavior into account, we are able to discriminate between the cells with high accuracy. The accuracy was larger for adult blood cells than for fetal blood cells. However, no significant difference was observed between donors of the two types.

KW - Deformation

KW - Microfluidic flow cytometry

KW - Neural network

KW - Red blood cell

KW - SlowFast

U2 - 10.1007/s10544-023-00688-6

DO - 10.1007/s10544-023-00688-6

M3 - Journal article

C2 - 38095813

AN - SCOPUS:85179627695

VL - 26

JO - Biomedical Microdevices

JF - Biomedical Microdevices

SN - 1387-2176

IS - 1

M1 - 5

ER -

ID: 377992186

Department of Clinical Medicine