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  • 标题:Phase contrast time-lapse microscopy datasets with automated and manual cell tracking annotations
  • 本地全文:下载
  • 作者:Dai Fei Elmer Ker ; Sungeun Eom ; Sho Sanami
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2018
  • 卷号:5
  • DOI:10.1038/sdata.2018.237
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image sequences, each spanning approximately 3.5 days, were generated with accompanying ground truths for C2C12 myoblast cells cultured under 4 different media conditions, including with fibroblast growth factor 2 (FGF2), bone morphogenetic protein 2 (BMP2), FGF2鈥?鈥塀MP2, and control (no growth factor). The ground truths generated contain information for tracking at least 3 parent cells and their descendants within these datasets and were validated using a two-tier system of manual curation. This comprehensive, validated dataset will be useful in advancing the development of computer-aided cell tracking algorithms and function as a benchmark, providing an invaluable opportunity to deepen our understanding of individual and population-based cell dynamics for biomedical research.
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