| 期刊全稱 | Artificial Intelligence in Label-free Microscopy | | 期刊簡稱 | Biological Cell Clas | | 影響因子2023 | Ata Mahjoubfar,Claire Lifan Chen,Bahram Jalali | | 視頻video | http://file.papertrans.cn/163/162476/162476.mp4 | | 發(fā)行地址 | 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 mul | | 圖書封面 |  | | 影響因子 | .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.. | | Pindex | Book 2017 |
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派博傳思國際
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發(fā)表于 2025-3-21 16:48:09
