Comparison of parameter-adapted segmentation methods for fluorescence micrographs

Held C, Palmisano R, Häberle L, Hensel M, Wittenberg T (2011)

Publication Status: Accepted

Publication Type: Journal article, Original article

Publication year: 2011

Journal

Cytometry Part A Wiley-Blackwell

Original Authors: Held C, Palmisano R, Häberle L, Hensel M, Wittenberg T

Publisher: Wiley-Blackwell

Book Volume: 79

Pages Range: 933-945

Journal Issue: 11

DOI: 10.1002/cyto.a.21122

Abstract

Interpreting images from fluorescence microscopy is often a time-consuming task with poor reproducibility. Various image processing routines that can help investigators evaluate the images are therefore useful. The critical aspect for a reliable automatic image analysis system is a robust segmentation algorithm that can perform accurate segmentation for different cell types. In this study, several image segmentation methods were therefore compared and evaluated in order to identify the most appropriate segmentation schemes that are usable with little new parameterization and robustly with different types of fluorescence-stained cells for various biological and biomedical tasks. The study investigated, compared, and enhanced four different methods for segmentation of cultured epithelial cells. The maximum-intensity linking (MIL) method, an improved MIL, a watershed method, and an improved watershed method based on morphological reconstruction were used. Three manually annotated datasets consisting of 261, 817, and 1,333 HeLa or L929 cells were used to compare the different algorithms. The comparisons and evaluations showed that the segmentation performance of methods based on the watershed transform was significantly superior to the performance of the MIL method. The results also indicate that using morphological opening by reconstruction can improve the segmentation of cells stained with a marker that exhibits the dotted surface of cells

Authors with CRIS profile

Ralf Palmisano Lehrstuhl für Experimentalphysik Thomas Wittenberg Technische Fakultät

Additional Organisation(s)

Optical Imaging Center Erlangen (OICE)

Related research project(s)

None - None Automated multi-dimensional, high-content image-analysis for fluorescence-microscopy (A04) (SFB 796) SFB 796: Steuerungsmechanismen mikrobieller Effektoren in Wirtszellen Jan. 1, 2009 - Dec. 31, 2017

Involved external institutions

Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE)

How to cite

APA:

Held, C., Palmisano, R., Häberle, L., Hensel, M., & Wittenberg, T. (2011). Comparison of parameter-adapted segmentation methods for fluorescence micrographs. Cytometry Part A, 79(11), 933-945. https://doi.org/10.1002/cyto.a.21122

MLA:

Held, Christian, et al. "Comparison of parameter-adapted segmentation methods for fluorescence micrographs." Cytometry Part A 79.11 (2011): 933-945.

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