PMID- 16382904 OWN - NLM STAT- MEDLINE DCOM- 20060118 LR - 20220310 IS - 0736-6205 (Print) IS - 0736-6205 (Linking) VI - 39 IP - 6 DP - 2005 Dec TI - Software for quantification of labeled bacteria from digital microscope images by automated image analysis. PG - 859-63 AB - 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. FAU - Selinummi, Jyrki AU - Selinummi J AD - Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. jyrki.selinummi@tut.fi FAU - Seppala, Jenni AU - Seppala J FAU - Yli-Harja, Olli AU - Yli-Harja O FAU - Puhakka, Jaakko A AU - Puhakka JA LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't PL - England TA - Biotechniques JT - BioTechniques JID - 8306785 SB - IM MH - Bioreactors MH - Colony Count, Microbial/*methods MH - Image Processing, Computer-Assisted/*methods MH - Microscopy MH - *Software EDAT- 2005/12/31 09:00 MHDA- 2006/01/19 09:00 CRDT- 2005/12/31 09:00 PHST- 2005/12/31 09:00 [pubmed] PHST- 2006/01/19 09:00 [medline] PHST- 2005/12/31 09:00 [entrez] AID - 000112018 [pii] AID - 10.2144/000112018 [doi] PST - ppublish SO - Biotechniques. 2005 Dec;39(6):859-63. doi: 10.2144/000112018.