title: Software for quantification of labeled bacteria from digital microscope images by automated image analysis.
abstract: Automated image analysis software, CellC, was developed and validated for quantification of bacterial cells from digital microscope images. CellC enables automated enumeration of bacterial cells, comparison of total count and specific count images [e.g., 4',6-diamino-2-phenylindole (DAPI) and fluorescence in situ hybridization (FISH) images], and provides quantitative estimates of cell morphology. The software includes an intuitive graphical user interface that enables easy usage as well as sequential analysis of multiple images without user intervention. Validation of enumeration reveals correlation to be better than 0.98 when total bacterial counts by CellC are compared with manual enumeration, with all validated image types. The software is freely available and modifiable: the executable files and MATLAB source codes can be obtained at www. cs. tut.fi/sgn/csb/cellc.
authors.affiliation: Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. jyrki.selinummi@tut.fi
authors.forename: Jyrki
authors.initials: J
authors.lastname: Selinummi
authors.forename: Jenni
authors.initials: J
authors.lastname: Seppälä
authors.forename: Olli
authors.initials: O
authors.lastname: Yli-Harja
authors.forename: Jaakko A
authors.initials: JA
authors.lastname: Puhakka
mesh_terms: D019149:Bioreactors; D015169:Colony Count, Microbial / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008853:Microscopy; D012984:Software