It’s an Easy-Peasy Tool for Cell Imaging!
CellProfiler 2.1 is a user-interactive, open source cell imaging analysis tool. There are various individual modules performing specific tasks, which can be put together to generate an image analysis pipeline. Users can then modify module parameters to generate the desired result. It is also really flexible, as it works on multiple platforms, such as Windows, Mac, and Linux. Furthermore, CellProfiler’s design is suitable for the high-content screening of thousands of images in batch modes on clusters.What is the Fuss About Image Segmentation?
The performance evaluating step for any image analysis pipeline is dependent on the algorithm you chose for optimally segmenting an image. In particular, segmentation clearly demarcates the boundaries between objects or cells, by distinguishing between the foreground and the background. Lastly, this is an important task, especially when you are trying to quantify single-cell based image measurements.Example: How to Count Labeled Bacterial Cells
Step 1
Mark the cell boundaries, using the IdentifyPrimaryObject module which detects the brightest objects (e.g. nuclei) against a dark background. It detects the darkest spots or centers of the cells, which are generally more uniform in staining, and is useful especially when cells are fluorescently labeled. To begin a new project in CellProfiler, select: File > New Project. Then to add a module, select: File > Add Module > Object Processing > IdentifyPrimaryObjects.
Figure 1: Adding IdentifyPrimaryObjects module to the pipeline.

Figure 2: The list of parameters for IdentifyPrimaryObjects module.
Step 2
The IdentifySecondaryObjects module identifies and marks cell boundaries using objects it sees in the IdentifyPrimaryObjects module, aka Step1.
Figure 3: The list of parameters for IdentifySecondaryObjects module.

Figure 4: Output of IdentifySecondaryObjects module. Image on top is the original image and the image at the bottom shows the segmention image.