Triini Olman

Abstract Droplet microfluidic methods used for microbiological experiments are fast, cost-effective, and provide high-throughput data. However, analysis of such image data can be difficult, and detection of molecular labels is limited by microscope parameters. Currently, there is lack of user-friendly methods to analyse a large volume of label-free droplet images without the need for trained personnel, or expensive, proprietary software.

Abstract The communal lifestyle of bacteria manifested as bacterial aggregation and potential biofilm formation is posing as a significant contributor to antimicrobial resistance. A key approach to adress the emerging pandemic is to implement novel techniques that enhance the precision and speed of analysis in various microbiological experiments.