Open AccessEstimating fluorescence lifetimes using extended Kalman filter
Author(s) -
Gao Kai,
Li David DayUei
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2017.1085
Subject(s) - extended kalman filter , kalman filter , computer science , monte carlo method , focus (optics) , signal (programming language) , gating , time domain , algorithm , artificial intelligence , computer vision , optics , physics , mathematics , physiology , statistics , biology , programming language
The extended Kalman filter (EKF) has been widely used in communication, signal processing and navigation control. In this Letter, the authors applied EKF, for the first time to their knowledge, to simultaneously estimate fluorescence lifetimes and instrument response functions (IRF) for time‐domain fluorescence lifetime imaging microscopy (FLIM) systems (we focus on gating and time‐correlated single‐photon counting techniques in this work). Monte‐Carlo simulations were performed to test its performances in comparison with previously reported methods. Simulation results show that the proposed algorithm can achieve comparable or better results than the others. More importantly, with EKF there is no need to measure the IRF of the FLIM system.