Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

12.4K Views

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08:58 min

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November 19th, 2018

DOI :

10.3791/58305-v

November 19th, 2018

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Jonghee Yoon¹, YoungJu Jo²^,³^,⁴^,⁷, Young Seo Kim³^,⁴^,⁵, Yeongjin Yu²^,³, Jiyeon Park⁶, Sumin Lee⁴, Wei Sun Park²^,³, YongKeun Park²^,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

Summary

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Keywords Label free

Lymphocyte Subtypes

3D Quantitative Phase Imaging

Machine Learning

Fluorescence Labeling

Flow Cytometry

Refractive Index Tomography

3D Quantitative Phase Microscope

RPMI Medium

Digital Micromirror Device

3D Reconstruction

Chapters in this video

0:04

Title

1:17

3D Quantitative Phase Imaging

4:34

Quantitative Morphological and Biochemical Feature Extraction and Supervised Learning and Identification

6:42

Results: Representative Label-Free Lymphocyte Subtype 3D Phase Imaging Identification

7:56

Conclusion

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