title: Semi-automated Acanthamoeba polyphaga detection and computation of Salmonella typhimurium concentration in spatio-temporal images.
abstract: 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.
authors.affiliation: Institute of Electronic Structure and Laser, Foundation for Research and Technology, P.O. Box 1527, Vassilika Vouton, 71110 Heraklion, Greece. tsibidis@iesl.forth.gr
authors.forename: George D
authors.initials: GD
authors.lastname: Tsibidis
authors.forename: Nigel J
authors.initials: NJ
authors.lastname: Burroughs
authors.forename: William
authors.initials: W
authors.lastname: Gaze
authors.forename: Elizabeth M H
authors.initials: EM
authors.lastname: Wellington
mesh_terms: D000048:Acanthamoeba / Q000166:cytology* / Q000254:growth & development / Q000302:isolation & purification; D001331:Automation / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods; D056265:Microbial Interactions; D008828:Microbiological Techniques / Q000379:methods*; D012486:Salmonella typhimurium / Q000254:growth & development / Q000302:isolation & purification; D059008:Time-Lapse Imaging / Q000379:methods