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010   $a3-319-51448-2
024 7 $a10.1007/978-3-319-51448-2
035   $a(CKB)3710000001177629
035   $a(DE-He213)978-3-319-51448-2
035   $a(MiAaPQ)EBC4844289
035   $a(PPN)200514407
035   $a(EXLCZ)993710000001177629
100   $a20170420d2017      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aArtificial Intelligence in Label-free Microscopy $eBiological Cell Classification by Time Stretch /$fby Ata Mahjoubfar, Claire Lifan Chen, Bahram Jalali
205   $a1st ed. 2017.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017.
215   $a1 online resource (XXXIII, 134 p. 52 illus. in color.) 
311   $a3-319-51447-4 
320   $aIncludes bibliographical references and index.
327   $aIntroduction -- 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.
330   $aThis 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.
606   $aBiomedical engineering
606   $aElectronics
606   $aMicroelectronics
606   $aOptical data processing
606   $aBioinformatics
606   $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X
606   $aElectronics and Microelectronics, Instrumentation$3https://scigraph.springernature.com/ontologies/product-market-codes/T24027
606   $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021
606   $aBioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15001
615  0$aBiomedical engineering.
615  0$aElectronics.
615  0$aMicroelectronics.
615  0$aOptical data processing.
615  0$aBioinformatics.
615 14$aBiomedical Engineering and Bioengineering.
615 24$aElectronics and Microelectronics, Instrumentation.
615 24$aImage Processing and Computer Vision.
615 24$aBioinformatics.
676   $a610.28
700   $aMahjoubfar$b Ata$4aut$4http://id.loc.gov/vocabulary/relators/aut$0933279
702   $aChen$b Claire Lifan$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aJalali$b Bahram$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254321303321
996   $aArtificial Intelligence in Label-free Microscopy$92100648
997   $aUNINA