The qBA algorithm was developed for quantitative analysis of 3-dimensional data of bacterial biofilms recorded by confocal laser scanning microscopy. Contrary to other biofilm analysing algorithms that are based on binary segmentation of the images, the bacteria are counted by this adaptive basic algorithm. The qBA algorithm transforms each 2D image into an inverted grayscale 3D image. The algorithm identifies local grayscale maxima upon two adjustable parameters (Prolongation (P) with dimension of pixels and Intensity (I) with dimension of the grey scale) assigning those to cell positions within the biofilm. The algorithm separately analyses and counts the bacteria of the green (nearly all cells) and red (dead cells) images of the Z-stacks and evaluates the viable cells that are defined as those cells that were only stained green.
Beside the bacteria counts, the algorithms additionally determines the area covered by biomatrial and its fractal distribution (lacunarity) as well as the biofilm thickness. These parameters are based on binary segmentation.
The latest version of the original source code can be provided via E-mail upon registration.
In order to register, please send an email (incl. your name and affiliation) to Mareike.Klinger@med.uni-jena.de
To use the code you will need to install ICE that can be downloaded from the homepage of the Computer Vision Group (Schiller University Jena).
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