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Immunology and Infection

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JoVE Journal Immunology and Infection
Label-gratis identificatie van lymfocyt subtypen met behulp van drie-dimensionale kwantitatieve fase Imaging en Machine Learning
 
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Label-gratis identificatie van lymfocyt subtypen met behulp van drie-dimensionale kwantitatieve fase Imaging en Machine Learning

Article DOI: 10.3791/58305-v • 08:58 min • November 19th, 2018
November 19th, 2018 •
1, 2,3,4,7, 3,4,5, 2,3, 6, 4, 2,3, 2,3,4
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

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Beschrijven we een protocol voor de identificatie van label-vrij van lymfocyt subtypen met behulp van kwantitatieve fase beeldvorming en een machinaal leren algoritme. Metingen van 3D refractive index tomograms van lymfocyten 3D morfologische en biochemische informatie voor individuele cellen, die vervolgens wordt geanalyseerd met een machine-leren algoritme voor de identificatie van celtypes presenteren.

Tags

Immunologie en infecties probleem 141 kwantitatieve fase imaging optische diffractie tomografie holotomography holografische microscopie lymfocyt identificatie immuun cel immunologie machinaal leren label-vrije imaging
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