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Optimal surface estimation and thresholding of confocal microscope images of biofilms using Beers Law
تخمین بهینه سطح و آستانه گرفتن تصاویر میکروسکوپ کانفوکال بیوفیلم ها با استفاده از قانون Beers -2020 Beers Law explains how light attenuates into thick specimens, including thick biofilms. We use a Bayesian
optimality criterion, the maximum of the posterior probability distribution, and computationally efficiently fit
Beers Law to the 3D intensity data collected from thick living biofilms by a confocal scanning laser microscope.
Using this approach the top surface of the biofilm and an optimal image threshold can be estimated. Biofilm
characteristics, such as bio-volumes, can be calculated from this surface. Results from the Bayesian approach are
compared to other approaches including the method of maximum likelihood or simply counting bright pixels.
Uncertainty quantification (i.e., error bars) can be provided for the parameters of interest. This approach is
applied to confocal images of stained biofilms of a common lab strain of Pseudomonas aeruginosa, stained biofilms
of Janthinobacterium isolated from the Antarctic, and biofilms of Staphylococcus aureus that have been genetically
modified to fluoresce green. Keywords: Attenuation | Thresholding | Maximum likelihood | Beer-Lambert Law | Bayesian | Confocal microscope image analysis |
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