Artificial Intelligence in Label-free Microscopy
Biological Cell Classification by Time Stretch
Nonfiction, Science & Nature, Technology, Electronics, Engineering, Health & Well Being, Medical
| Author: | Ata Mahjoubfar, Claire Lifan Chen, Bahram Jalali | ISBN: | 9783319514482 |
| Publisher: | Springer International Publishing | Publication: | April 19, 2017 |
| Imprint: | Springer | Language: | English |
| Author: | Ata Mahjoubfar, Claire Lifan Chen, Bahram Jalali |
| ISBN: | 9783319514482 |
| Publisher: | Springer International Publishing |
| Publication: | April 19, 2017 |
| Imprint: | Springer |
| Language: | English |
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.
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.
