Journal
MICRON
Volume 42, Issue 8, Pages 911-920Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.micron.2011.06.010
Keywords
2D Imaging; Automated image analysis; Organism detection; Time-lapse microscopy; Bacteria counting
Categories
Funding
- Biotechnology and Biological Sciences Research Council [D18179] Funding Source: Medline
- Biotechnology and Biological Sciences Research Council [D18179] Funding Source: researchfish
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Interaction between bacteria and protozoa is an increasing area of interest, however there are a few systems that allow extensive observation of the interactions. A semi-automated approach is proposed to analyse a large amount of experimental data and avoid a time demanding manual object classification. We examined a surface system consisting of non nutrient agar with a uniform bacterial lawn that extended over the agar surface, and a spatially localised central population of amoebae. Location and identification of protozoa and quantification of bacteria population are performed by the employment of image analysis techniques in a series of spatial images. The quantitative tools are based on intensity thresholding, or on probabilistic models. To accelerate organism identification, correct classification errors and attain quantitative details of all objects a custom written Graphical User Interfaces has also been developed. (C) 2011 Elsevier Ltd. All rights reserved.
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