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Dynamic range and background filtering in raster image correlation spectroscopy
Author(s) -
DE METS R.,
DELON A.,
BALLAND M.,
DESTAING O.,
WANG I.
Publication year - 2020
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12925
Subject(s) - raster graphics , autocorrelation , raster scan , background subtraction , microscope , filter (signal processing) , subtraction , digital image correlation , image subtraction , fluorescence correlation spectroscopy , range (aeronautics) , image resolution , optics , materials science , biological system , artificial intelligence , image processing , computer science , image (mathematics) , computer vision , pixel , physics , fluorescence , mathematics , statistics , arithmetic , biology , binary image , composite material
Summary Raster‐scan image correlation spectroscopy (RICS) enables researchers to measure molecular translational diffusion constants and concentrations from standard confocal laser scanning microscope images and is suitable for measuring a wide range of mobility, especially fast‐diffusing molecules. However, as RICS analysis is based on the spatial autocorrelation function of fluorescence images, it is sensitive to the presence of fluorescent structures within the image. In this study, we investigate methods to filter out immobile or slow moving background structures and their impact on RICS results. Both the conventional moving‐average subtraction‐based method and cross‐correlation subtraction‐based method are rationalized and quantified. Simulated data and experimental measurements in living cells stress the importance of optimizing the temporal resolution of background filtering for reliable RICS measurements. Finally, the capacity of RICS analysis to separate two species is studied.