Author Affiliations
1 Institute of Modern Optics, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Nankai University, Tianjin 300350, China
2 Nanophotonics Research Centre, Institute of Microscale Optoelectronics & State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen 518060, China
Cell identification and sorting have been hot topics recently. However, most conventional approaches can only predict the category of a single target, and lack the ability to perform multitarget tasks to provide coordinate information of the targets. This limits the development of high-throughput cell screening technologies. Fortunately, artificial intelligence (AI) systems based on deep-learning algorithms provide the possibility to extract hidden features of cells from original image information. Here, we demonstrate an AI-assisted multitarget processing system for cell identification and sorting. With this system, each target cell can be swiftly and accurately identified in a mixture by extracting cell morphological features, whereafter accurate cell sorting is achieved through noninvasive manipulation by optical tweezers. The AI-assisted model shows promise in guiding the precise manipulation and intelligent detection of high-flux cells, thereby realizing semi-automatic cell research.
AI algorithm cell identification and sorting optical tweezers microfluidic chip 
Chinese Optics Letters
2023, 21(11): 110009

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