Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells
In this study, Chen et al. introduced a new deep learning-based method termed flimGANE to rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. flimGANE is particularly useful in fundamental biological research and clinical applications.
Main Authors: | , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-01-01
|
Series: | Communications Biology |
Online Access: | https://doi.org/10.1038/s42003-021-02938-w |