• DocumentCode
    1343845
  • Title

    Automated Analysis of Fluorescence Lifetime Imaging Microscopy (FLIM) Data Based on the Laguerre Deconvolution Method

  • Author

    Pande, Paritosh ; Jo, Javier A.

  • Author_Institution
    Dept. of Biomed. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    58
  • Issue
    1
  • fYear
    2011
  • Firstpage
    172
  • Lastpage
    181
  • Abstract
    In fluorescence lifetime imaging microscopy (FLIM), fluorescence time decay at each pixel of the imaged sample are measured. Every recorded fluorescence decay corresponds to the time convolution of the instrument response with the intrinsic fluorescence impulse response function (IRF), from which the sample fluorescence lifetime is determined. To estimate the IRF, the instrument response thus needs to be deconvolved from the recorded fluorescence decay. We have recently introduced a novel FLIM time-deconvolution method based on the linear expansion of the fluorescence decays on an orthonormal Laguerre basis. Since this method allows simultaneous estimation of the IRFs at all pixels, it performs at least two orders of magnitude faster than standard algorithms. In its original implementation, however, the Laguerre basis, determined by the Laguerre parameter , is selected using a heuristic approach. Here, we present an automated implementation, whereby the Laguerre parameter is treated as a free parameter within a nonlinear least squares optimization scheme. The new implementation combines the unmatched inherent computational speed of the Laguerre deconvolution method with a systematic model selection approach. This method will thus facilitate applications of FLIM requiring automatic estimation of the spatial distribution of fluorescence lifetimes, such as in in vivo tissue FLIM imaging.
  • Keywords
    biomedical optical imaging; deconvolution; fluorescence spectroscopy; least squares approximations; medical signal processing; optical microscopy; optimisation; stochastic processes; FLIM data automated analysis; FLIM time deconvolution method; IRF estimation; Laguerre deconvolution method; Laguerre parameter; automated implementation; fluorescence decay linear expansion; fluorescence lifetime imaging microscopy; fluorescence lifetime spatial distribution; fluorescence time decay; heuristic approach; impulse response function; in in vivo tissue FLIM imaging; instrument response time convolution; intrinsic fluorescence IRF; nonlinear least squares optimization; orthonormal Laguerre basis; Deconvolution; Estimation; Fluorescence; Imaging; Instruments; Pixel; Signal to noise ratio; Fluorescence lifetime imaging microscopy (FLIM); Laguerre expansion of the kernel technique; in vivo imaging; time deconvolution; Algorithms; Carotid Stenosis; Coronary Vessels; Humans; Image Processing, Computer-Assisted; Least-Squares Analysis; Luminescent Agents; Microscopy, Fluorescence; Reproducibility of Results; Statistics, Nonparametric;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2010.2084086
  • Filename
    5594996