Seeing More: A Future of Augmented Microscopy

被引:15
|
作者
Sullivan, Devin P. [1 ]
Lundberg, Emma [1 ]
机构
[1] KTH Royal Inst Technol, Sch Engn Sci Chem Biotechnol & Hlth, Sci Life Lab, S-17121 Stockholm, Sweden
关键词
D O I
10.1016/j.cell.2018.04.003
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Microscope images are information rich. In this issue of Cell, Christiansen et al. show that label-free images of cells can be used to predict fluorescent labels representing cell type, state, and organelle distribution using a deep-learning framework. This paves the way for computationally multiplexed assays derived from inexpensive label-free microscopy.
引用
收藏
页码:546 / 548
页数:3
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