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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-...

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Detaylı Bibliyografya
Asıl Yazarlar: Mahjoubfar, Ata (Yazar), Chen, Claire Lifan (Yazar), Jalali, Bahram (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2017.
Imprint: Springer,
Edisyon:1st ed. 2017.
Konular:
Online Erişim:Full-text access
Diğer Bilgiler
Özet: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.
Fiziksel Özellikler:XXXIII, 134 p. 52 illus. in color. online resource.
ISBN:9783319514482
DOI:10.1007/978-3-319-51448-2