首页 | 本学科首页   官方微博 | 高级检索  
     


Noise‐Corrected Principal Component Analysis of fluorescence lifetime imaging data
Authors:Alix Le Marois  Simon Labouesse  Klaus Suhling  Rainer Heintzmann
Affiliation:1. +44 020 7848 2119+44 020 7848 2420;2. Department of Physics, King's College London, London, United Kingdom;3. Institute Fresnel, Marseille, France;4. Leibniz Institute of Photonic Technology, Jena, Germany;5. Institute of Physical Chemistry, Abbe Centre of Photonics, Friedrich Schiller University Jena, Jena, Germany
Abstract:Fluorescence Lifetime Imaging (FLIM) is an attractive microscopy method in the life sciences, yielding information on the sample otherwise unavailable through intensity‐based techniques. A novel Noise‐Corrected Principal Component Analysis (NC‐PCA) method for time‐domain FLIM data is presented here. The presence and distribution of distinct microenvironments are identified at lower photon counts than previously reported, without requiring prior knowledge of their number or of the dye's decay kinetics. A noise correction based on the Poisson statistics inherent to Time‐Correlated Single Photon Counting is incorporated. The approach is validated using simulated data, and further applied to experimental FLIM data of HeLa cells stained with membrane dye di‐4‐ANEPPDHQ. Two distinct lipid phases were resolved in the cell membranes, and the modification of the order parameters of the plasma membrane during cholesterol depletion was also detected.

Noise‐corrected Principal Component Analysis of FLIM data resolves distinct microenvironments in cell membranes of live HeLa cells.

Keywords:Confocal fluorescence microscopy  fluorescence lifetime imaging  data processing  global analysis  live cell imaging  Poisson noise correction
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号