Automated Acanthamoeba polyphaga detection and computation of Salmonella typhimurium concentration in spatio-temporal images

TL;DR

This paper presents an automated image analysis system for detecting Acanthamoeba polyphaga and estimating Salmonella typhimurium concentrations in spatio-temporal images, facilitating detailed observation of bacteria-protozoa interactions.

Contribution

It introduces a two-tiered automated analysis approach combining thresholding-based algorithms with user reclassification for studying bacteria and amoebae interactions.

Findings

Automated detection of amoebae, cysts, and bacteria coverage in spatial images.

Effective classification and counting achieved with minimal user intervention.

System enables detailed analysis of protozoa-bacteria interactions over time.

Abstract

Interactions between bacteria and protozoa is an increasing area of interest, however there are a few systems that allow extensive observation of the interactions. 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. The amoeba fed on bacteria and migrated over the plate. Automated image analysis techniques were used to locate and count amoebae, cysts and bacteria coverage in a series of spatial images. Most algorithms were based on intensity thresholding, or a modification of this idea with probabilistic models. Our strategy was two tiered, we performed an automated analysis for object classification and bacteria counting followed by user intervention/reclassification using custom written Graphical User Interfaces.