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Label-free droplet image analysis with Cellprofiler
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Researchers developed a label-free droplet image analysis workflow using CellProfiler to enable high-throughput processing of droplet microfluidics images without requiring molecular labels or expensive proprietary software. The approach makes droplet microfluidic technology more accessible for a broader range of biological and microbiological applications.
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. Such methods would make droplet microfluidic technology more widely accessible for a larger range of biological applications. In this paper we demonstrate an image analysis pipeline designed using Cellprofiler™, a free, open-source software. This pipeline identifies water-in-oil microfluidic droplets, microplastic particles, and bacterial growth without using fluorescent or other labels.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.