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Noise-Corrected Principal Component Analysis of fluorescence lifetime imaging data

Abstract : Fluorescence Lifetime Imaging (FLIM) is an attractivemicroscopy method in the life sciences, yielding informa-tion on the sample otherwise unavailable through inten-sity-based techniques. A novel Noise-Corrected PrincipalComponent Analysis (NC-PCA) method for time-domainFLIM data is presented here. The presence and distribu-tion of distinct microenvironments are identified at lowerphoton counts than previously reported, without requir-ing prior knowledge of their number or of the dye’s decaykinetics. A noise correction based on the Poisson statisticsinherent to Time-Correlated Single Photon Counting isincorporated. The approach is validated using simulateddata, and further applied to experimental FLIM data ofHeLa cells stained with membrane dye di-4-AN-EPPDHQ. Two distinct lipid phases were resolved in thecell membranes, and the modification of the order para-meters of the plasma membrane during cholesterol deple-tion was also detected.
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Submitted on : Monday, April 16, 2018 - 9:12:17 AM
Last modification on : Monday, November 29, 2021 - 3:39:02 PM

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Alix Le Marois, Simon Labouesse, Klaus Suhling, Rainer Heintzmann. Noise-Corrected Principal Component Analysis of fluorescence lifetime imaging data. Journal of Biophotonics, 2017, 10 (9), pp.1124 - 1133. ⟨10.1002/jbio.201600160⟩. ⟨hal-01767262⟩



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