Applied and Environmental Microbiology vol:76 issue:5 pages:1615-1622
Quantification and sizing of filamentous cyanobacteria in environmental samples or cultures are timeconsuming
and are often performed by using manual or semiautomated microscopic analysis. Automation of
conventional image analysis is difficult because filaments may exhibit great variations in length and patchy
autofluorescence. Moreover, individual filaments frequently cross each other in microscopic preparations, as
deduced by modeling. This paper describes a novel approach based on object-oriented image analysis to
simultaneously determine (i) filament number, (ii) individual filament lengths, and (iii) the cumulative
filament length of unbranched cyanobacterial morphotypes in fluorescent microscope images in a fully automated
high-throughput manner. Special emphasis was placed on correct detection of overlapping objects by
image analysis and on appropriate coverage of filament length distribution by using large composite images.
The method was validated with a data set for Planktothrix rubescens from field samples and was compared with
manual filament tracing, the line intercept method, and the Utermohl counting approach. The computer
program described allows batch processing of large images from any appropriate source and annotation of
detected filaments. It requires no user interaction, is available free, and thus might be a useful tool for basic
research and drinking water quality control.