Investigation of Different Free Image Analysis Software for High-Throughput Droplet Detection

Abstract

Droplet microfluidics has revealed innovative strategies in biology and chemistry. This advancement has delivered novel quantification methods, such as digital droplet polymerase chain reaction (ddPCR) and antibiotic heteroresistance analysis tool. For droplet analysis, researchers often use imaging techniques. Unfortunately, the analysis of images may require specific tools or programming skills to produce the expected results. In order to address the issue, we explore the potential use of standalone freely available software to detect droplets. We select four most popular software and classify them into instinctive and objective types based on their operation logic. We test and evaluate the software's i) ability to detect droplets, ii) accuracy and precision, and iii) overall user-friendliness. In our experimental setting we find the objective type of software is better suited for droplet detection. The objective type of software also has simpler workflow or pipeline, especially aimed for non-experienced user. In our case, CellProfilerTM (CP) offers the most user-friendly experience for both single image and batch processing analysis.