Fluorescence lifetime studies of NO2. I. Excitation of the perturbed 2B2 state near 600 nm

1977 ◽  
Vol 66 (9) ◽  
pp. 4100-4110 ◽  
Author(s):  
V. M. Donnelly ◽  
F. Kaufman
Keyword(s):  
Fluorescence Lifetime ◽  
Lifetime Studies

Multiphoton imaging and fluorescence lifetime studies on unstained cells and tissue at cryogenic conditions

2007 ◽  
Author(s):  
Martin Stark ◽  
Daniel Dörr ◽  
Alexander Ehlers ◽  
Daniel Sauer ◽  
Rainer Bückle ◽  
...  
Keyword(s):  
Fluorescence Lifetime ◽  
Multiphoton Imaging ◽  
Lifetime Studies ◽  
Cryogenic Conditions

Electro-optical and fluorescence lifetime studies of aminophthalimide probes in liquids

1995 ◽  
Author(s):  
Nicolai A. Nemkovich ◽  
Wolfram Baumann ◽  
Alexander S. Kozlovski ◽  
Heribert Reis
Keyword(s):  
Fluorescence Lifetime ◽  
Lifetime Studies

Fluorescence lifetime studies of MeV erbium implanted silica glass

1991 ◽  
Vol 27 (11) ◽  
pp. 993-995 ◽  
Author(s):  
A. Lidgard ◽  
A. Polman ◽  
D.C. Jacobsen ◽  
G.E. Blonder ◽  
R. Kistler ◽  
...  
Keyword(s):  
Fluorescence Lifetime ◽  
Silica Glass ◽  
Lifetime Studies

scholarly journals Ultra-fast fit-free analysis of complex fluorescence lifetime imaging via deep learning

2019 ◽  
Author(s):  
Jason T. Smith ◽  
Ruoyang Yao ◽  
Nattawut Sinsuebphon ◽  
Alena Rudkouskaya ◽  
Joseph Mazurkiewicz ◽  
...  
Keyword(s):  
Deep Learning ◽  
Fluorescence Lifetime ◽  
Biomedical Applications ◽  
Quantitative Information ◽  
Clinical Settings ◽  
Fluorescence Lifetime Imaging ◽  
Complex Data ◽  
Lifetime Imaging ◽  
Lifetime Studies ◽  
Quantities Of Interest

AbstractFluorescence lifetime imaging (FLI) provides unique quantitative information in biomedical and molecular biology studies, but relies on complex data fitting techniques to derive the quantities of interest. Herein, we propose a novel fit-free approach in FLI image formation that is based on Deep Learning (DL) to quantify complex fluorescence decays simultaneously over a whole image and at ultra-fast speeds. Our deep neural network (DNN), named FLI-Net, is designed and model-based trained to provide all lifetime-based parameters that are typically employed in the field. We demonstrate the accuracy and generalizability of FLI-Net by performing quantitative microscopic and preclinical experimental lifetime-based studies across the visible and NIR spectra, as well as across the two main data acquisition technologies. Our results demonstrate that FLI-Net is well suited to quantify complex fluorescence lifetimes, accurately, in real time in cells and intact animals without any parameter settings. Hence, it paves the way to reproducible and quantitative lifetime studies at unprecedented speeds, for improved dissemination and impact of FLI in many important biomedical applications, especially in clinical settings.

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