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
N1 - © 2023. The Author(s).
PY - 2023/12/14
Y1 - 2023/12/14
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 - Hydrodynamics
KW - Microfluidic Analytical Techniques
KW - Erythrocytes
KW - Microfluidics
KW - Fetus
UR - http://www.scopus.com/inward/record.url?scp=85179627695&partnerID=8YFLogxK
U2 - 10.1007/s10544-023-00688-6
DO - 10.1007/s10544-023-00688-6
M3 - Journal article
C2 - 38095813
SN - 1387-2176
VL - 26
JO - Biomedical Microdevices
JF - Biomedical Microdevices
IS - 1
M1 - 5
ER -