Quantifying cellular characteristics from a large heterogeneous population is essential to identify rare, disease-driving cells. A recent development in the combination of high-throughput screening microscopy with single-cell profiling provides an unprecedented opportunity to decipher disease-driving phenotypes. Accurately and instantly processing large amounts of image data, however, remains a technical challenge when an analysis output is required minutes after data acquisition. Here, we present fast and accurate real-time cell tracking (FACT). FACT can segment â¼20,000 cells in an average of 2.5Â s (1.9-93.5 times faster than the state of the art). It can export quantifiable features minutes after data acquisition (independent of the number of acquired image frames) with an average of 90%-96% precision. We apply FACT to identify directionally migrating glioblastoma cells with 96% precision and irregular cell lineages from a 24Â h movie with an average F1 score of 0.91.
Instant processing of large-scale image data with FACT, a real-time cell segmentation and tracking algorithm.
利用 FACT(一种实时细胞分割和跟踪算法)即时处理大规模图像数据
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作者:Chou Ting-Chun, You Li, Beerens Cecile, Feller Kate J, Storteboom Jelle, Chien Miao-Ping
| 期刊: | Cell Reports Methods | 影响因子: | 4.500 |
| 时间: | 2023 | 起止号: | 2023 Nov 20; 3(11):100636 |
| doi: | 10.1016/j.crmeth.2023.100636 | 研究方向: | 细胞生物学 |
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