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AI-assisted real-time parallel cell sorting with holographic optical trapping

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【作者】 邓如平; 卢开鹏; 杨嘉豪; 豆秀婕; 吴晓静; 闵长俊; 袁武; 张聿全; 袁小聪; 刘伟伟;

【Author】 Ruping Deng;Kaipeng Lu;Jiahao Yang;Xiujie Dou;Xiaojing Wu;ChangJun Min;Wu Yuan;Yuquan Zhang;Xiaocong Yuan;Weiwei Liu;Institute of Modern Optics, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Nankai University;Nanophotonics Research Centre, Institute of Microscale Optoelectronics & State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University;School of Integrated Circuits, Harbin Institute of Technology (Shenzhen);Department of Public Health, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University;Department of Biomedical Engineering, The Chinese University of Hong Kong;

【通讯作者】 张聿全;刘伟伟;

【机构】 Institute of Modern Optics, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Nankai University; Nanophotonics Research Centre, Institute of Microscale Optoelectronics & State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University; School of Integrated Circuits, Harbin Institute of Technology (Shenzhen); Department of Public Health, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University; Department of Biomedical Engineering, The Chinese University of Hong Kong;

【摘要】 Live cell sorting enables the acquisition of highly purified and functionally preserved populations for applications in disease diagnosis, stem cell research, and precision medicine. However, achieving high-efficiency and fully automated sorting remains challenging. Here, we present a real-time parallel AI holographic optical tweezer(PAIHOT) system that integrates YOLOv11n detection with Kalman filtering and class-matching for stable multi-target tracking and prediction in real time.Predicted trajectories guide the optical trap to the cell periphery, thereby reducing photodamage compared to conventional center-focused trapping. Experimental results demonstrated that PAIHOT achieves sorting purities exceeding 91% across multiple cell types, and the viability assays confirm intact morphology and strong growth activity. The PAIHOT enables highaccuracy, parallel, and low-damage cell sorting in dynamic microscopic environments, providing an effective and robust platform for intelligent, high-throughput single-cell research.

【Abstract】 Live cell sorting enables the acquisition of highly purified and functionally preserved populations for applications in disease diagnosis, stem cell research, and precision medicine. However, achieving high-efficiency and fully automated sorting remains challenging. Here, we present a real-time parallel AI holographic optical tweezer(PAIHOT) system that integrates YOLOv11n detection with Kalman filtering and class-matching for stable multi-target tracking and prediction in real time.Predicted trajectories guide the optical trap to the cell periphery, thereby reducing photodamage compared to conventional center-focused trapping. Experimental results demonstrated that PAIHOT achieves sorting purities exceeding 91% across multiple cell types, and the viability assays confirm intact morphology and strong growth activity. The PAIHOT enables highaccuracy, parallel, and low-damage cell sorting in dynamic microscopic environments, providing an effective and robust platform for intelligent, high-throughput single-cell research.

【基金】 supported by the Shenzhen Medical Research Fund (No. D250403001);the National Natural Science Foundation of China (Nos. 62375177, 62575184, and 82172699);the Shenzhen Science and Technology Program(No. RCJC20210609103232046);the Project of DEGP(No. 2024ZDZX2019);the Research Team Cultivation Program of Shenzhen University (No. 2023QNT014)
  • 【文献出处】 Chinese Optics Letters ,中国光学快报(英文版) , 编辑部邮箱 ,2026年06期
  • 【分类号】TP18;Q-05
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