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Autore: | Mahjoubfar Ata |
Titolo: | Artificial Intelligence in Label-free Microscopy : Biological Cell Classification by Time Stretch / / by Ata Mahjoubfar, Claire Lifan Chen, Bahram Jalali |
Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
Edizione: | 1st ed. 2017. |
Descrizione fisica: | 1 online resource (XXXIII, 134 p. 52 illus. in color.) |
Disciplina: | 610.28 |
Soggetto topico: | Biomedical engineering |
Electronics | |
Microelectronics | |
Optical data processing | |
Bioinformatics | |
Biomedical Engineering and Bioengineering | |
Electronics and Microelectronics, Instrumentation | |
Image Processing and Computer Vision | |
Persona (resp. second.): | ChenClaire Lifan |
JalaliBahram | |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | 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. |
Sommario/riassunto: | 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. |
Titolo autorizzato: | Artificial Intelligence in Label-free Microscopy |
ISBN: | 3-319-51448-2 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910254321303321 |
Lo trovi qui: | Univ. Federico II |
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