title: A fast, fully automated cell segmentation algorithm for high-throughput and high-content screening.
abstract: 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.
authors.affiliation: Image Mining Group, Institut Pasteur Korea, Hawolgok-dong, Seongbuk-gu, Seoul 136-791, Korea. dfenistein@yahoo.com
authors.forename: D
authors.initials: D
authors.lastname: Fenistein
authors.forename: B
authors.initials: B
authors.lastname: Lenseigne
authors.forename: T
authors.initials: T
authors.lastname: Christophe
authors.forename: P
authors.initials: P
authors.lastname: Brodin
authors.forename: A
authors.initials: A
authors.lastname: Genovesio