期刊
COMMUNICATIONS BIOLOGY
卷 5, 期 1, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s42003-021-02938-w
关键词
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资金
- NSF [2041345]
- Welch Foundation [F-1833]
- NIH [GM129617, EY033106]
- Texas 4000 Foundation
- Texas Health Catalyst Program at Dell Medical School
- CPRIT [RR160005]
- University Graduate Continuing Fellowship at UT Austin
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [2041345] Funding Source: National Science Foundation
In this study, Chen et al. introduced a new deep learning-based method called 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.
Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and that flimGANE provides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Forster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability, flimGANE is particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical. 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.
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