Artificial intelligence in label-free microscopy : biological cell classification by time stretch

• Main Authors: Mahjoubfar, Ata (Author), Chen, Claire Lifan (Author), Jalali, B. (Author)
• Format: Electronic eBook
• Language: English
• Published: Cham, Switzerland : Springer, 2017.
• Subjects: Artificial intelligence > Biological applications.; Microscopy.; elektronické knihy; electronic books
• ISBN: 9783319514482; 9783319514475
• Physical Description: 1 online resource (xxxiii, 134 pages) : color illustrations
• Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty

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.