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

页码：958 / 964

页数：7

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