Design of Droplet Microfluidic Sorting and Counting System based on Object Detection and Tracking Algorithm

Pengjian Wang(School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences University of Chinese Academy of Sciences)
Xianqiang Mi(School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences University of Chinese Academy of Sciences)

Abstract

Droplet microfluidics, which encapsulates individual cells within separate microreactors, has become an essential tool for single-cell phenotypic and genotypic analysis. However, the efficiency of single-cell encapsulation is limited by the Poisson distribution governing the encapsulation process, resulting in most droplets being either empty or containing multiple cells. Traditional single-cell sorting methods typically rely on fluorescence labeling for identification, but this approach not only increases experimental costs and complexity but can also impact cell viability. Additionally, current label-free sorting methods still encounter difficulties in accurately detecting multicellular droplets and small cellular aggregates. To address these challenges, this paper proposes an intelligent sorting system that combines YOLOv8 object detection and BoTSORT tracking algorithms. This system enables real-time analysis of droplet images, facilitating precise identification, counting, and automated sorting of target droplets. To validate the system's performance, polystyrene microspheres were used to simulate real cells in sorting tests. The results demonstrated that, under label-free conditions, the system significantly outperformed traditional fluorescence labeling methods in both classification accuracy and sorting efficiency. This system provides an effective, label-free solution for cell sorting, with potential applications in precision medicine, single-cell sequencing, and drug screening.

Keywords

droplet sorting; droplet microfluidics; object detection; object tracking; image recognition

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https://github.com/ultralytics/ultralytics

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DOI: http://dx.doi.org/10.26549/met.v8i1.23688