Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms

Wiesmann V, Bergler M, Franz D, Palmisano R, Prinzen M, Wittenberg T (2017)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2017

Journal

BMC Bioinformatics BMC

Book Volume: 18

Pages Range: 176

Journal Issue: 1

DOI: 10.1186/s12859-017-1591-2

Open Access Link: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1591-2

Abstract

Manual assessment and evaluation of fluorescent micrograph cell experiments is time-consuming and tedious. Automated segmentation pipelines can ensure efficient and reproducible evaluation and analysis with constant high quality for all images of an experiment. Such cell segmentation approaches are usually validated and rated in comparison to manually annotated micrographs. Nevertheless, manual annotations are prone to errors and display inter- and intra-observer variability which influence the validation results of automated cell segmentation pipelines.

Authors with CRIS profile

Matthias Bergler Chair of Visual Computing (LGDV) Daniela Franz Professur für Visual Computing Ralf Palmisano Optical Imaging Center Erlangen (OICE) Thomas Wittenberg Chair of Visual Computing (LGDV)

Involved external institutions

Fraunhofer-Institut für Integrierte Schaltungen (IIS)

Germany (DE)

How to cite

APA:

Wiesmann, V., Bergler, M., Franz, D., Palmisano, R., Prinzen, M., & Wittenberg, T. (2017). Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms. BMC Bioinformatics, 18(1), 176. https://doi.org/10.1186/s12859-017-1591-2

MLA:

Wiesmann, Veit, et al. "Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms." BMC Bioinformatics 18.1 (2017): 176.

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