Artificial Intelligence in Label-free Microscopy: Biological Cell Classification by Time Stretch

Artificial Intelligence in Label-free Microscopy: Biological Cell Classification by Time Stretch

Author
Ata Mahjoubfar, Claire Lifan Chen, Bahram Jalali (auth.)
Publisher
Springer International Publishing
Language
English
Edition
1
Year
2017
Page
XXXIII, 134
ISBN
978-3-319-51447-5, 978-3-319-51448-2
File Type
pdf
File Size
4.8 MiB

This book introduces time-stretch quantitative phase imaging (TS-QPI), a high-throughput label-free imaging flow cytometer developed for big data acquisition and analysis in phenotypic screening. TS-QPI is able to capture quantitative optical phase and intensity images simultaneously, enabling high-content cell analysis, cancer diagnostics, personalized genomics, and drug development. The authors also demonstrate a complete machine learning pipeline that performs optical phase measurement, image processing, feature extraction, and classification, enabling high-throughput quantitative imaging that achieves record high accuracy in label -free cellular phenotypic screening and opens up a new path to data-driven diagnosis.

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