Artificial neural network approaches for fluorescence lifetime imaging techniques

Wu, Gang and Nowotny, Thomas and Zhang, Yongliang and Yu, Hongqi and Li, David Day-Uei (2016) Artificial neural network approaches for fluorescence lifetime imaging techniques. Optics Letters, 41 (11). pp. 2561-2564. ISSN 0146-9592

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    Abstract

    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.

    ORCID iDs

    Wu, Gang, Nowotny, Thomas, Zhang, Yongliang, Yu, Hongqi and Li, David Day-Uei ORCID logoORCID: https://orcid.org/0000-0002-6401-4263;