Mahjoubfar, Ata. <br/><br/>
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 | 
<br/><br/> 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. 
<br/><br/><label>ISBN: </label>9783319514482 
<br/><br/><label>Subjects--Topical Terms: </label><br/>EXTC Engineering
<br/><br/><label>Subjects--Index Terms: </label>Biomedical Engineering and Bioengineering. Electronics and Microelectronics, Instrumentation. Image Processing and Computer Vision. Bioinformatics. 
<br/><br/><label>Dewey Class. No.: </label>610.28