Mahjoubfar, Ata.
Artificial Intelligence in Label-free Microscopy Biological Cell Classification by Time Stretch / [electronic resource] : - 1st ed. 2017. - XXXIII, 134 p. 52 illus. in color. | Binding - Card Paper |
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.
9783319514482
EXTC Engineering
Biomedical Engineering and Bioengineering. Electronics and Microelectronics, Instrumentation. Image Processing and Computer Vision. Bioinformatics.
610.28
Artificial Intelligence in Label-free Microscopy Biological Cell Classification by Time Stretch / [electronic resource] : - 1st ed. 2017. - XXXIII, 134 p. 52 illus. in color. | Binding - Card Paper |
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.
9783319514482
EXTC Engineering
Biomedical Engineering and Bioengineering. Electronics and Microelectronics, Instrumentation. Image Processing and Computer Vision. Bioinformatics.
610.28