
pmid: 28391814
Disk diffusion testing, known as antibiogram, is widely applied in microbiology to determine the antimicrobial susceptibility of microorganisms. The measurement of the diameter of the zone of growth inhibition of microorganisms around the antimicrobial disks in the antibiogram is frequently performed manually by specialists using a ruler. This is a time-consuming and error-prone task that might be simplified using automated or semi-automated inhibition zone readers. However, most readers are usually expensive instruments with embedded software that require significant changes in laboratory design and workflow.Based on the workflow employed by specialists to determine the antimicrobial susceptibility of microorganisms, we have designed a software tool that, from images of disk diffusion tests, semi-automatises the process. Standard computer vision techniques are employed to achieve such an automatisation.We present AntibiogramJ, a user-friendly and open-source software tool to semi-automatically determine, measure and categorise inhibition zones of images from disk diffusion tests. AntibiogramJ is implemented in Java and deals with images captured with any device that incorporates a camera, including digital cameras and mobile phones. The fully automatic procedure of AntibiogramJ for measuring inhibition zones achieves an overall agreement of 87% with an expert microbiologist; moreover, AntibiogramJ includes features to easily detect when the automatic reading is not correct and fix it manually to obtain the correct result.AntibiogramJ is a user-friendly, platform-independent, open-source, and free tool that, up to the best of our knowledge, is the most complete software tool for antibiogram analysis without requiring any investment in new equipment or changes in the laboratory.
Electronic Data Processing, Acinetobacter, Staphylococcus, Computational Biology, Reproducibility of Results, Microbial Sensitivity Tests, Anti-Bacterial Agents, Diffusion, Automation, User-Computer Interface, Enterobacteriaceae, Pseudomonas, Programming Languages, Enterococcus, Software
Electronic Data Processing, Acinetobacter, Staphylococcus, Computational Biology, Reproducibility of Results, Microbial Sensitivity Tests, Anti-Bacterial Agents, Diffusion, Automation, User-Computer Interface, Enterobacteriaceae, Pseudomonas, Programming Languages, Enterococcus, Software
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 46 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
