Seeing More: A Future of Augmented Microscopy
Author(s) -
Devin P. Sullivan,
Emma Lundberg
Publication year - 2018
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2018.04.003
Subject(s) - biology , microscopy , organelle , fluorescence microscope , proteome , sted microscopy , fluorescence , electron microscope , computational biology , superresolution , microbiology and biotechnology , nanotechnology , artificial intelligence , computer science , bioinformatics , physics , image (mathematics) , optics , materials science
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom