N-cell Droplet Encapsulation Recognition via Weakly Supervised Counting Network

Droplet-based microfluidic platforms arouse an increasing attention in various biomedical research by providing the isolated micro environment for biochemical reactions. Accordingly, it is of great significance to monitor and control the amount of the contents, e.g. cells or microbeads, inside each droplet. In this paper, we develop a novel weakly supervised algorithm to recognize droplets encapsulating diverse amount of cells (N-cell droplet encapsulation) from highly adherent droplet images. Quantitative experimental results exhibit that our approach can not only distinguish N-cell droplet encapsulations, but also locate each cell without any supervised 10-cation information.