CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

• Published in: Source code for biology and medicine Vol. 8; no. 1; p. 16
• Main Authors: Hodneland, Erlend, Kögel, Tanja, Frei, Dominik Michael, Gerdes, Hans-Hermann, Lundervold, Arvid
• Format: Journal Article
• Language: English
• Published: London BioMed Central 09.08.2013; BioMed Central Ltd
• Subjects: Bioinformatics; Biomedical and Life Sciences; Cells; Comparative analysis; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Cytology; Fluorescence microscopy; Image processing; Imaging systems; Life Sciences; Methodology; Methods; Technology application; High-throughput; Automated analysis; CellSegm; Nucleus staining; Surface staining; Cell segmentation
• ISSN: 1751-0473; 1751-0473
• DOI: 10.1186/1751-0473-8-16

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm , the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm . The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab , offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.