
Using CellX to Quantify Intracellular Events
Abstract
Methods to quantify features of individual cells using light microscopy have become widely used in biology. A multitude of computational tools has been developed for image analysis; however, they are often only for specific cell types and microscopy techniques. This unit describes CellX, an open-source software package for cell segmentation, intensity quantification, and cell tracking on a variety of microscopy images. CellX can perform cell segmentation largely independently of cell shapes, and can also cope with images that are crowded with cells. The basic protocol describes how to use CellX for cell segmentation and quantification. This protocol remains the same whether there is a collection of images to be analyzed or whether cell tracking on a sequence of images is to be performed. The CellX output comprises control images for visual validation, text files for post-processing statistics, and MATLAB objects for advanced subsequent analysis. Curr. Protoc. Mol. Biol. 101:14.22.114.22.20. © 2013 by John Wiley & Sons, Inc.
Keywords: image analysis; segmentation; tracking; microscopy; single cell quantification
Figures
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Figure 14.22.8 Screenshot of CellX batch processing tab. The top-down order of text fields and buttons corresponds to the order of the protocol steps 18 to 27. -

Figure 14.22.9 Screenshots of successful seeding results. Left panel: almost perfect seeding (only two false positive seeds appear). Right panel: perfect seeding (no false positive seeds appear). -

Figure 14.22.10 Screenshot of bad seeding results. Left panel: few seeds appear. Right panel: many false positive seeds appear.
Videos
Literature Cited
| Literature Cited | |
| Carpenter, A.E., Jones, T.R., Lamprecht, M.R., Clarke, C., Kang, I.H., Friman, O., Guertin, D.A., Chang, J.H., Lindquist, R.A., Moffat, J., Golland, P., and Sabatini, D.M. 2009. CellProfiler: Image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 7:R100. | |
| Collins, T.J. 2007. ImageJ for microscopy. BioTechniques 43:S25-S30. | |
| Gordon, A., Colman-Lerner, A., Chin, T.E., Benjamin, K.R., Yu, R.C., and Brent, R. 2007. Single-cell quantification of molecules and rates using open-source microscope-based cytometry. Nat. Methods 4:175-181. | |
| Kvarnstrom, M., Logg, K., Diez, A., Bodvard, K., and Kall, M. 2008. Image analysis algorithms for cell contour recognition in budding yeast. Opt. Express 17:1294312957. | |
| Locke, J.C.W. and Elowitz, M.B. 2006. Using movies to analyse gene circuit dynamics in single cells. Nat. Rev. Microbiol. 7:383392. | |












