成像流式细胞术的诊断潜力。
Diagnostic Potential of Imaging Flow Cytometry.
机构信息
Imaging Platform at the Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA.
School of Science and Technology, Nazarbayev University, Kababnbay batyr avenue 53, 010000, Astana, Kazakhstan; A.N. Belozersky Institute of Physico-Chemical Biology/Biological Faculty, M.V. Lomonosov Moscow State University, 119991, Moscow, Russian Federation.
出版信息
Trends Biotechnol. 2018 Jul;36(7):649-652. doi: 10.1016/j.tibtech.2017.12.008. Epub 2018 Jan 31.
Imaging flow cytometry (IFC) captures multichannel images of hundreds of thousands of single cells within minutes. IFC is seeing a paradigm shift from low- to high-information-content analysis, driven partly by deep learning algorithms. We predict a wealth of applications with potential translation into clinical practice.
成像流式细胞术 (IFC) 可在数分钟内捕获数十万个单细胞的多通道图像。IFC 正从低信息含量分析向高信息含量分析转变，这在一定程度上是由深度学习算法推动的。我们预测将会有大量的应用，具有潜在的临床转化价值。
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