CellSegm - high-throughput 3D cell segmentation (in MATLAB)
Project coordinator / PI: PhD Erlend Hodneland
Segmentation of cells using nucleus markers in 2D. A) Raw surface stain, B) raw nucleus stain, C) surface stain minus nucleus stain, D) markers (blue) derived from the nucleus stain superimposed onto the surface stain, E) cell markers, F) smoothed segmentation image, from G) watershed image, H) detected cell areas (Figure 9 from Hodneland et al. 2013).
CellSegm, developed at Department of Biomedicine/MIC, 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, and has the ability to detect various types of surface stained cells in 3D.
Major algorithmic steps are:
(ii) Hessian-based ridge enhancement
(iii) Marker-controlled watershed segmentation
(iv) Feature-based classfication of cell candidates
After detection and outlining of individual cells, the cell candidates can be subject to further analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. Segmentation of tissue samples having appropriate characteristics can also be performed 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.
Links to data
The MATLAB code and test data are hosted and maintained at GitHub - https://github.com/ehodneland/cellsegm
Test - 26: Cerebellum, homo - 32958396.svs
To get started, see further details and code examples at: Hodneland E, Kögel T, Frei DM, Gerdes HH, Lundervold A. CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation. Source Code for Biology and Medicine 2013 Aug 9;8(1):16 (link, PDF)
This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.