one of the most important techniques in microbial ecology,
since this is the
most direct approach to examine the microbe's world from
its own perspective, at spatial scales relevant to the microbes
themselves. A major challenge in microbial ecology is to
develop reliable and facile methods of computer-assisted microscopy
that can analyze complex digital images of microbial
populations and communities at single cell resolution, and compute ecologically important quantitative
characteristics of their abundance, spatial organization, and diversity without
cultivation. There are several advantages of using pattern
recognition techniques in conjunction with computer-assisted
microscopy and digital image analysis for quantitative studies
of microbial communities. Automatic image analysis reduces the
amount of tedious work with microscopes needed to accurately measure microbial
abundance and their morphotype classification in situ. These techniques
performed by CMEIAS provide a powerful quantitative approach to analyze
ecophysiological and spatial features that complement molecular microbial ecology approaches to analyze complex microbial
situ without cultivation.
software is developed by a team of microbial ecologists, computer scientists and mathematicians at the MSU Center for Microbial Ecology. The core analytical program consists
of several custom plug-ins that we have built for UTHSCSA
ImageTool, a free image analysis software operating on
a personal computer running 32- or 64-bit Windows operating system.
The CMEIAS-IT Ver.
1.28 object analyzer extracts any user-selected combination of up to 34 measurement attributes (size, shape, luminosity and spatial coordinates) of each foreground object found in the image. The CMEIAS/IT 1-dimensional object classifier selectively groups objects within an image into up to 16 bins based on division of a scale defined by the upper class limits of a single measurement feature, in units defined by user-specified spatial calibration. The CMEIAS morphotype classifier automatically categorizes each foreground object
in the image into one of 11 predominant
microbial morphotypes, including cocci, spirals, curved rods,
U-shaped rods, regular straight rods, unbranched filaments, ellipsoids,
clubs, rods with extended prostheca, rudimentary branched
rods, and branched filaments. The CMEIAS image analysis program
and comprehensive testing results of its morphotype classification
algorithms are described in detail in Liu et
1.28 software is released as a free image analysis program that provides wide applications in microbial ecology
research, training and education. A comprehensive operator
manual plus interactive training tutorials providing background
information and instructions to use this software are included
with the CMEIAS-IT Ver. 1.28 program files available in the download
A stand-alone CMEIAS Color Segmentation application toolkit is now available to facilitate the image editing tasks required to segment and analyze foreground objects within complex images.
A stand-alone CMEIAS Quadrat Maker program is designed to help optimize the grid-lattice dimensions that divide landscape images into equal sized quadrats for plot-based spatial pattern analysis.
A Java-based CMEIAS JFrad program is designed to analyze the self-similar fractal dimensions of complex landscape architectures, e.g., microbial biofilms.
Several CMEIAS audio-visual *.wmv demos are available to introduce the main features of CMEIAS software, e.g., Color Segmentation, Quadrat Maker, and JFrad.
A major CMEIAS Image Analysis
upgrade is currently under
development and will be available at a future date. Periodically check the CMEIAS News page for update announcements.