Title:	An image‑processing method to detect sub‑optical features based on understanding noise in intensity measurements
Authors:	Bhatia, Tripta
Keywords:	Fluid lamellar phase Image noise Optimum smoothening Signal-to-noise ratio Tubules
Issue Date:	Jul-2018
Publisher:	Springer International Publishing
Citation:	European Biophysics Journal with Biophysics Letters, 2018 Vol. 47, p531–538
Abstract:	Accurate quantitative analysis of image data requires that we distinguish between fluorescence intensity (true signal) and the noise inherent to its measurements to the extent possible. We image multilamellar membrane tubes and beads that grow from defects in the fluid lamellar phase of the lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine dissolved in water and water-glycerol mixtures by using fluorescence confocal polarizing microscope. We quantify image noise and determine the noise statistics. Understanding the nature of image noise also helps in optimizing image processing to detect sub-optical features, which would otherwise remain hidden. We use an image-processing technique "optimum smoothening" to improve the signal-to-noise ratio of features of interest without smearing their structural details. A high SNR renders desired positional accuracy with which it is possible to resolve features of interest with width below optical resolution. Using optimum smoothening, the smallest and the largest core diameter detected is of width [Formula: see text] and [Formula: see text] nm, respectively, discussed in this paper. The image-processing and analysis techniques and the noise modeling discussed in this paper can be used for detailed morphological analysis of features down to sub-optical length scales that are obtained by any kind of fluorescence intensity imaging in the raster mode.
Description:	Open Access
URI:	http://hdl.handle.net/2289/7118
ISSN:	0175-7571 1432-1017
Alternative Location:	https://doi.org/10.1007/s00249-017-1273-z)
Copyright:	© The Author(s) 2018
Appears in Collections:	Research Papers (SCM)

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