Chen Biqi, Yin Zi, Ng Billy Wai-Lung, Wang Dan Michelle, Tuan Rocky S, Bise Ryoma, Ker Dai Fei Elmer
Institute for Tissue Engineering and Regenerative Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, School of Medicine, Zhejiang University, Hangzhou, China.
Npj Imaging. 2024 Oct 7;2(1):41. doi: 10.1038/s44303-024-00046-y.
Label-free, live cell recognition (i.e. instance segmentation) and tracking using computer vision-aided recognition can be a powerful tool that rapidly generates multi-modal readouts of cell populations at single cell resolution. However, this technology remains hindered by the lack of accurate, universal algorithms. This review presents related biological and computer vision concepts to bridge these disciplines, paving the way for broad applications in cell-based diagnostics, drug discovery, and biomanufacturing.
使用计算机视觉辅助识别进行无标记活细胞识别（即实例分割）和跟踪，可能是一种强大的工具，能够在单细胞分辨率下快速生成细胞群体的多模态读数。然而，这项技术仍然受到缺乏准确通用算法的阻碍。本综述介绍了相关的生物学和计算机视觉概念，以弥合这些学科之间的差距，为基于细胞的诊断、药物发现和生物制造的广泛应用铺平道路。
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