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03262nam a22005175i 4500 |
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978-3-319-51448-2 |
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DE-He213 |
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20170420173107.0 |
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cr nn 008mamaa |
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170420s2017 gw | s |||| 0|eng d |
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|a 9783319514482
|9 978-3-319-51448-2
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|a 10.1007/978-3-319-51448-2
|2 doi
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|2 bisacsh
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|a 610.28
|2 23
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|a Mahjoubfar, Ata.
|e author.
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|a Artificial Intelligence in Label-free Microscopy
|h [electronic resource] :
|b Biological Cell Classification by Time Stretch /
|c by Ata Mahjoubfar, Claire Lifan Chen, Bahram Jalali.
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| 264 |
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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| 300 |
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|a XXXIII, 134 p. 52 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|a online resource
|b cr
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|a text file
|b PDF
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|a 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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|a 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.
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|a Engineering.
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|a Image processing.
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| 650 |
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|a Bioinformatics.
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| 650 |
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|a Electronics.
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| 650 |
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|a Microelectronics.
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| 650 |
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|a Biomedical engineering.
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4 |
|a Engineering.
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| 650 |
2 |
4 |
|a Biomedical Engineering.
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| 650 |
2 |
4 |
|a Electronics and Microelectronics, Instrumentation.
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| 650 |
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|a Image Processing and Computer Vision.
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| 650 |
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|a Bioinformatics.
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| 700 |
1 |
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|a Chen, Claire Lifan.
|e author.
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| 700 |
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|a Jalali, Bahram.
|e author.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer eBooks
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| 776 |
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8 |
|i Printed edition:
|z 9783319514475
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| 856 |
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|u http://dx.doi.org/10.1007/978-3-319-51448-2
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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