A fast, fully automated cell segmentation algorithm for high-throughput and high-content screening

被引：38
|
作者：
Fenistein, D. [1 ]
Lenseigne, B. [1 ]
Christophe, T. [2 ]
Brodin, P. [3 ]
Genovesio, A. [1 ]
机构：
[1] Inst Pasteur Korea, Image Min Grp, Seoul 136791, South Korea
[2] Inst Pasteur Korea, Screening Technol & Pharmacol Grp, Seoul 136791, South Korea
[3] Inst Pasteur Korea, Inserm Equipe Avenir Biol Intracellular Pathogen, Seoul 136791, South Korea
来源：
CYTOMETRY PART A | 2008年 / 73A卷 / 10期
关键词：
image analysis; biological image processing; automation; cytometry; object detection; segmentation; high-content screening;
D O I：
10.1002/cyto.a.20627
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
High-throughput, high-content screening (HT-HCS) of large compound libraries for drug discovery imposes new constraints on image analysis algorithms. Time and robustness are paramount while accuracy is intrinsically statistical. In this article, a fast and fully automated algorithm for cell segmentation is proposed. The algorithm is based on a strong attachment to the data that provide robustness and have been validated on the HT-HCS of large compound libraries and different biological assays. We present the algorithm and its performance, a description of its advantages and limitations, and a discussion of its range of application. (C) 2008 International Society for Advancement of Cytometry.
引用
收藏
页码：958 / 964
页数：7
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