Estimating fluorescence lifetimes using the expectation-maximisation algorithm

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The expectation-maximisation (EM) algorithm uses incomplete data to get the estimation of the probabilistic model parameter, and it has been widely used in machine learning. EM techniques are applied to estimate fluorescence lifetimes in time-correlated single-photon counting based fluorescence lifetime imaging experiments without measuring the instrument response functions. The results of Monte Carlo simulations indicate that the proposed approach can obtain better or comparable accuracy and precision performances than the previously reported method.
Original languageEnglish
Pages (from-to)1-2
Number of pages2
JournalElectronics Letters
Issue number1
Publication statusPublished - 11 Jan 2018


  • fluorescence
  • expectation-maximization algorithm
  • Monte Carlo simulations


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