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Image analysis in fluorescence microscopy: Bacterial dynamics as a case study
Author(s) -
van Teeffelen Sven,
Shaevitz Joshua W.,
Gitai Zemer
Publication year - 2012
Publication title -
bioessays
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.175
H-Index - 184
eISSN - 1521-1878
pISSN - 0265-9247
DOI - 10.1002/bies.201100148
Subject(s) - microscopy , fluorescence microscope , computer science , live cell imaging , image processing , image (mathematics) , living cell , artificial intelligence , photoactivated localization microscopy , computational biology , biological system , computer vision , multiphoton fluorescence microscope , biology , fluorescence , optics , cell , physics , genetics
Fluorescence microscopy is the primary tool for studying complex processes inside individual living cells. Technical advances in both molecular biology and microscopy have made it possible to image cells from many genetic and environmental backgrounds. These images contain a vast amount of information, which is often hidden behind various sources of noise, convoluted with other information and stochastic in nature. Accessing the desired biological information therefore requires new tools of computational image analysis and modeling. Here, we review some of the recent advances in computational analysis of images obtained from fluorescence microscopy, focusing on bacterial systems. We emphasize techniques that are readily available to molecular and cell biologists but also point out examples where problem‐specific image analyses are necessary. Thus, image analysis is not only a toolkit to be applied to new images but also an integral part of the design and implementation of a microscopy experiment.