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Artificial Intelligence in Label-free Microscopy Biological Cell Classification by Time Stretch /
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-...
| Main Authors: | , , |
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| Corporate Author: | |
| Format: | e-Book |
| Language: | English |
| Published: |
Cham :
Springer International Publishing :
2017.
Imprint: Springer, |
| Edition: | 1st ed. 2017. |
| Subjects: | |
| Online Access: | Full-text access |
| Summary: | 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. • Demonstrates how machine learning is used in high-speed microscopy imaging to facilitate medical diagnosis; • Provides a systematic and comprehensive illustration of time stretch technology; • Enables multidisciplinary application, including industrial, biomedical, and artificial intelligence. |
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| Physical Description: | XXXIII, 134 p. 52 illus. in color. online resource. |
| ISBN: | 9783319514482 |
| DOI: | 10.1007/978-3-319-51448-2 |