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A novel high-speed fluorescence lifetime imaging (FLIM) analysis method based on artificial neural networks (ANN) has been proposed. The proposed ANN-FLIM method does not require iterative searching procedures or initial conditions, which are usually required for traditional FLIM methods. In terms of image generation, ANN-FLIM is free from iterative computations and able to generate lifetime images at least 180-fold faster than conventional least squares curve-fitting approaches. The advantages of ANN-FLIM were demonstrated on both synthesized and experimental data, showing that it has great potential to fuel current revolutions in rapid FLIM technologies.
- fluorescence lifetime imaging microscopy
Wu, G., Nowotny, T., Zhang, Y., Yu, H., & Li, D. D-U. (2016). Artificial neural network approaches for fluorescence lifetime imaging techniques. Optics Letters, 41(11), 2561-2564. https://doi.org/10.1364/OL.41.002561