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Upgraded User-Friendly Image-Activated Microfluidic Cell Sorter Using an Optimized and Fast Deep Learning Algorithm.
- Source :
- Micromachines; Dec2022, Vol. 13 Issue 12, p2105, 10p
- Publication Year :
- 2022
-
Abstract
- Image-based cell sorting is essential in biological and biomedical research. The sorted cells can be used for downstream analysis to expand our knowledge of cell-to-cell differences. We previously demonstrated a user-friendly image-activated microfluidic cell sorting technique using an optimized and fast deep learning algorithm. Real-time isolation of cells was carried out using this technique with an inverted microscope. In this study, we devised a recently upgraded sorting system. The cell sorting techniques shown on the microscope were implemented as a real system. Several new features were added to make it easier for the users to conduct the real-time sorting of cells or particles. The newly added features are as follows: (1) a high-resolution linear piezo-stage is used to obtain in-focus images of the fast-flowing cells; (2) an LED strobe light was incorporated to minimize the motion blur of fast-flowing cells; and (3) a vertical syringe pump setup was used to prevent the cell sedimentation. The sorting performance of the upgraded system was demonstrated through the real-time sorting of fluorescent polystyrene beads. The sorter achieved a 99.4% sorting purity for 15 μ m and 10 μ m beads with an average throughput of 22.1 events per second (eps). [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2072666X
- Volume :
- 13
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Micromachines
- Publication Type :
- Academic Journal
- Accession number :
- 161038217
- Full Text :
- https://doi.org/10.3390/mi13122105