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Etikett-fri identifiering av lymfocyter undertyper med hjälp av tredimensionell kvantitativ fas Imaging och Machine Learning
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1Department of Physics,University of Cambridge, 2Department of Physics,Korea Advanced Institute of Science and Technology, 3KAIST Institute for Health Science and Technology,Korea Advanced Institute of Science and Technology, 4Tomocube, Inc., 5Department of Chemical and Biomolecular Engineering,Korea Advanced Institute of Science and Technology, 6Department of Biological Sciences,Korea Advanced Institute of Science and Technology, 7Department of Applied Physics,Stanford University
Chapters
- 00:04Title
- 01:173D Quantitative Phase Imaging
- 04:34Quantitative Morphological and Biochemical Feature Extraction and Supervised Learning and Identification
- 06:42Results: Representative Label-Free Lymphocyte Subtype 3D Phase Imaging Identification
- 07:56Conclusion
Vi beskriver ett protokoll för etikett-fri identifiering av lymfocyter subtyper använder kvantitativa fas imaging och en algoritm för maskininlärning. Mätningar av 3D brytningsindex tomograms av lymfocyter presentera 3D morfologiska och biokemiska information för enskilda celler, som sedan analyseras med en maskininlärning algoritmen för identifiering av celltyper.
