Measuring object intensity and shape

Last updated on 2026-03-31 | Edit this page

Overview

Questions

  • Once we have segmentation masks, what can CellProfiler measure from them?
  • What is the difference between intensity measurements and shape measurements?

Objectives

  • Use MeasureObjectIntensity to quantify fluorescence per nucleus, cell, and cytoplasm.
  • Use MeasureObjectSizeShape to quantify area/shape descriptors for each object.

Measuring: turning segmentations into numbers

So far, we have been creating masks: pixels belonging to nuclei, cells, and cytoplasm. Masks are useful on their own for quality control, but the real power of CellProfiler is that it can turn masks into quantitative measurements.

In this episode, we will measure two broad classes of features:

  1. Intensity features: “how bright is this object in a given channel?”
    • Example questions:
      • Is actin intensity higher in treated cells?
      • Do nuclei become brighter/dimmer in the DNA channel?
  2. Size and shape features: “what is the geometry of this object?”
    • Example questions:
      • Do cells spread out or shrink?
      • Do nuclei become larger or more elongated?

MeasureObjectIntensity: measuring fluorescence per object

Add the MeasureObjectIntensity module to your pipeline.

This module measures per-object intensity statistics for one or more images. For example, it can quantify the DNA stain in the nucleus, or the actin stain intensity in the cytoplasm.

Challenge

Challenge

What channel should be measured in what part of the cell? For example, should we quantify DNA signal only in the nucleus, or everywhere (nucleus, cytoplasm, whole cell)? Discuss with your neighbor.

The simplest setup is to measure all channels in all parts of the cells and decide which measurements to interpret down the line. Perhaps surprisingly, this is the approach frequently chosen in high-throughput experiments: measure everything, ask questions later. And indeed, one can envision scenarios where measuring e.g. DNA in the cytoplasm may prove useful if DNA leaks through the nuclear envelope due to environmental stress.

That said, if you have a narrow research question and an idea of where to look for changes in cell morphology, then only measuring the correct combination of channel and cell components will be the right approach.

To set this up in CellProfiler, for Select the objects to measure select:

  • Nuclei_Filtered
  • Cells
  • Cytoplasm
Callout

Note: these names may differ, depending on what you called them in previous modules. We will not use the nuclei created in IdentifyPrimaryObjects, because we filtered them in IdentifySecondaryObjects to only contain nuclei of cells that are not touching the image boundary.

Then, select all channels in Select images to measure, unless you would like to only measure some of the channels. Finally, run the module in test mode and look at the output.

Challenge

Challenge

Let’s see whether the DNA intensity is higher in the cytoplasm or the nucleus. Using the table that the module outputs in test mode, look for a row with DNA - Cytoplasm - MeanIntensity and read off the value in the Mean column. Then repeat this for DNA - Nuclei_Filtered - MeanIntensity. What do you observe?

Depending on your segmentation settings and which image you are using to test, the mean DNA intensity is about 3-4x higher in nuclei than in the cytoplasm, as you would expect.

MeasureObjectSizeShape: measuring geometry

Beyond fluorescence intensities, it is common to measure shape descriptors of cells. Example measurements include:

  • area
  • perimeter
  • eccentricity / elongation
  • compactness

Once again, we add the module (MeasureObjectSizeShape) and select our objects to measure in as before. For this workshop, disable Zernike and advanced features, as they slow down CellProfiler, which can be annoying while building the pipeline.

Callout

CellProfiler measures many things - including some with names that most will never have heard of. The helps a lot with deciphering the measurement names. For example, for eccentricity it contains this helpful image: Circles that are increasingly stretched into long ovals. Beneath the circles are values for eccentricity, which go from 0 (perfect circle) toward 1 (extremely stretched oval). Which shows that eccentricity will be higher for elongated cells.

Step 3: Sanity check measurements

When building a workflow, it is worthwhile checking outputs at each step. For measurements this can be a bit harder than with segmentation, but one of the things we can check is the cytoplasm/nucleus area ratio. We have now seen many example images of these MCF7 cells and could venture a guess that the cytoplasm occupies more space than the nuclei (in 2D).

Challenge

Calculate the cytoplasm/nucleus ratio

Run the module in test mode and look for the Area feature for Cytoplasm and Nuclei_Filtered (or equivalent names in your pipeline). This feature describes the average number of pixels occupied by the cytoplasm/nucleus. Now calculate the ratio of the cytoplasm to nucleus area.

The cytoplasm occupies about 3-4x more space than the nucleus. Again, depending on your segmentation settings, your result may differ. This is in line with our observations from images of the cells.

Exporting measurements

So far we have created segmentation masks and computed measurements (intensity and size/shape). To use these measurements outside CellProfiler (e.g. in R, Python, or Excel), we need to export them to files. One standard way to do this is the ExportToSpreadsheet module.

Add the ExportToSpreadsheet module. For this workshop, the default settings are fine. The most important thing is that:

  • the module exports object-level measurements (for Nuclei_Filtered, Cells, and Cytoplasm), and
  • you need to know where the files are written to.
Challenge

Challenge: export your measurements

  1. Add ExportToSpreadsheet at the end of your pipeline.
  2. Run the pipeline (not in test mode, but by clicking Analyze images)
  3. Find the exported files on disk.

Questions: - What file format(s) were produced (e.g. .csv)? - Do you get separate files for Nuclei_Filtered, Cells, and Cytoplasm? - Open up one of the files. Can you identify at least one column coming from intensity measurements and one coming from shape measurements?

With default settings, CellProfiler typically exports one spreadsheet per object type (e.g. one for nuclei, one for cells, one for cytoplasm), plus one for image-level measurements if any were computed.

Open one of the exported spreadsheets and look for column names such as:

  • Intensity_MeanIntensity_* or Intensity_IntegratedIntensity_* (from MeasureObjectIntensity)
  • AreaShape_Area / AreaShape_Perimeter / AreaShape_Eccentricity (from MeasureObjectSizeShape)

If you cannot find the files, check the Output file location setting in ExportToSpreadsheet and re-run the pipeline.

Callout

Tip: run on a subset first

When developing a pipeline, it’s often faster to run on a small subset of images first to confirm that exports look correct. Once you’re satisfied, run the pipeline on the full dataset. In this exercise, you have only been provided with a few images so this does not apply, but it will make a big difference when dealing with hundreds of images.

Conclusions

We have now added measurement modules to compute:

  • per-object fluorescence intensities (per nucleus, cell, cytoplasm)
  • per-object morphology features (size and shape)

These features are the raw material for downstream analyses like comparing treated vs control populations, building morphological profiles, or training classifiers.

Help

Did you get stuck with one of the steps? Download a working version of the pipeline here:

Download pipeline

Callout

If you are using Firefox, you have to right click the button and select Save Link As....

After downloading the pipeline, you can compare it to yours for troubleshooting. To do so, first open a new CellProfiler window. Then, import this pipeline in CellProfiler by clicking on File > Import > Pipeline from File.

Key Points
  • MeasureObjectIntensity quantifies fluorescence per object; choose objects and channels deliberately.
  • MeasureObjectSizeShape quantifies morphology; disable Zernike/advanced features to iterate faster.