首页|Instant multicolor super-resolution microscopy with deep convolutional neural network

Instant multicolor super-resolution microscopy with deep convolutional neural network

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Multicolor super-resolution (SR) microscopy plays a critical role in cell biology research and can visual-ize the interactions between different organelles and the cytoskeleton within a single cell.However,more color channels bring about a heavier budget for imaging and sample preparation,and the use of fluorescent dyes of higher emission wavelengths leads to a worse spatial resolution.Recently,deep convolutional neural networks (CNNs) have shown a compelling capability in cell segmentation,super-resolution reconstruction,image restoration,and many other aspects.Taking advantage of CNN's strong representational ability,we devised a deep CNN-based instant multicolor super-resolution im-aging method termed IMC-SR and demonstrated that it could be used to separate different biological components labeled with the same fluorophore,and generate multicolor images from a single super-resolution image in silico.By IMC-SR,we achieved fast three-color live-cell super-resolution imaging with ～100 nm resolution over a long temporal duration,revealing the complicated interactions between multiple organelles and the cytoskeleton in a single COS-7 cell.

Multicolor imagingSuper-resolutionConvolutional neural network

Songyue Wang、Chang Qiao、Amin Jiang、Di Li、Dong Li

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National Laboratory of Biomacromolecules,CAS Center for Excellence in Biomacromolecules,Institute of Bio-physics,Chinese Academy of Sciences,Beijing 100101,China

College of Life Sciences,University of Chinese Academy of Sciences,Beijing 100049,China

Department of Automation,Tsinghua University,Beijing 100084,China

Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences,University of Science and Technology of China,Hefei 230026,China

Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory),Guangzhou 510005,China

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2017YFA05053013182780231770930ZDBS-LY-SM004

2021

生物物理学报
中国生物物理学会 中国科学院生物物理研究所

生物物理学报

影响因子：0.355
ISSN：1000-6737
年,卷(期)：2021.7(4)
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