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Artificial Intelligence in Label-free Microscopy
Údaje o názvu Artificial Intelligence in Label-free Microscopy [electronic resource] : Biological Cell Classification by Time Stretch / by Ata Mahjoubfar, Claire Lifan Chen, Bahram Jalali. Nakladatel Cham : Springer International Publishing : Imprint: Springer, 2017. Fyz.popis XXXIII, 134 p. 52 illus. in color. online resource. ISBN 9783319514482 Úplný obsah Introduction -- Background -- Nanometer-resolved imaging vibrometer -- Three-dimensional ultrafast laser scanner -- Label-free High-throughput Phenotypic Screening -- Time Stretch Quantitative Phase Imaging -- Big data acquisition and processing in real-time -- Deep Learning and Classification -- Optical Data Compression in Time Stretch Imaging -- Design of Warped Stretch Transform -- Concluding Remarks and Future Work -- References. Poznámky k dostupnosti Přístup pouze pro oprávněné uživatele Dal.odpovědnost Chen, Claire Lifan. Jalali, Bahram. Dal.odpovědnost SpringerLink (Online service) Předmět.hesla Engineering. * Image processing. * Bioinformatics. * Electronics. * Microelectronics. * Biomedical engineering. Forma, žánr elektronické knihy electronic books Země vyd. Německo Jazyk dok. angličtina Druh dok. Elektronické knihy URL Plný text pro studenty a zaměstnance UPOL kniha
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.
Introduction -- Background -- Nanometer-resolved imaging vibrometer -- Three-dimensional ultrafast laser scanner -- Label-free High-throughput Phenotypic Screening -- Time Stretch Quantitative Phase Imaging -- Big data acquisition and processing in real-time -- Deep Learning and Classification -- Optical Data Compression in Time Stretch Imaging -- Design of Warped Stretch Transform -- Concluding Remarks and Future Work -- References.
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