Artificial Intelligence in Label-free Microscopy

Biological Cell Classification by Time Stretch

Claire Lifan Chen, Bahram Jalali, Ata Mahjoubfar, et al.

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Medizin

Beschreibung

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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Schlagwörter

warped time stretch, silicon photonics, ultrafast and high-throughput data acquisition, real-time instruments for biomedical applications, High-throughput multivariate sensing