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Artificial Intelligence in Label-Free Microscopy: Biological Cell Classification by Time Stretch
Bahram Jalali
(Author)
·
Ata Mahjoubfar
(Author)
·
Claire Lifan Chen
(Author)
·
Springer
· Paperback
Artificial Intelligence in Label-Free Microscopy: Biological Cell Classification by Time Stretch - Mahjoubfar, Ata ; Chen, Claire Lifan ; Jalali, Bahram
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Synopsis "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-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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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
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