In nature, bacteria are predominantly found as surface-associated cell assemblages known as biofilms.
In biofilms, bacteria do not become fundamentally different just in terms of their physiology and gene expression, they also acquire high resistance to antibiotics and a variety of antimicrobials.
Although the existence of biofilms has been documented for years, only recently have powerful tools for investigating them in situ been developed. One such tool is imaging using confocal laser scanning microscopy (CLSM) in combination with specific fluorescent stains.
CLSM explores the distribution and structure of biofilms in 2-D and 3-D, producing relatively large amounts of high resolution image data.
The amount of data acquired by CLSM calls for automatic image analysis methods which are both accurate and time-saving, in order that the visual information can be transformed into numbers.
bioImage_L is a novel image analysis software for the automatic characterization of the structure and distribution of biofilms. The novel feature of bioImage_L is the inclusion of an algorithm that automatically identifies color tonalities without having to make a prior monochrome conversion into separate RGB channels.
The sub-populations identified by color image segmentation are processed independently by algorithms that calculate commonly–used image analysis parameters, e.g., biovolume, mean thickness, and substratum coverage.
bioImage_L has been developed with the common user in mind, as no prior knowledge of sophisticated image analysis software is required.
The main menu offers different operations in 2 dimensions and 3 dimensions:
See the related article: Chávez de Paz LE. Image analysis software based on color segmentation for characterization of viability and physiological activity of biofilms. Appl Environ Microbiol. 2009 Mar;75(6):1734-9.
For instructions on how to obtain bioImage_L, go to the section 'Get bioImage_L'.
bioImage_L was developed using the MATLAB GUIDE tool (Matlab - R2008a) and is available for Windows as a stand-alone application.