Looking for a module to REMOVE objects from further analysis

Hi,

I’m designing a pipeline to analyze photos of human macrophages and fibrocytes, two closely related cell types in the same population.

I’d like to be able to design a pipeline that
A) Identified macrophages, then
B) Removes the macrophages from further analysis and
C) Allows me to identify the remaining fibrocytes with another “IdentifyPrimaryObjects” module.

In short, I want to identify macrophages, tell cell profiler not to include macrophages in a subsequent analysis, and then use the resulting image to identify fibrocytes.

Then I can figure out the staining intensity for each cell type.

I’ll upload a sample image and the pipeline I’ve constructed.

TL;DR
I need a module that let’s me discard objects that meet previously defined parameters.

Thanks very much,

Michael


adjusted filter objects.cpproj (240 KB)

Hi Michael,

Perhaps MaskImage is the module you’re looking for? You can use it to remove a object set of choice from an image; the resultant image can then be used to identify further objects and the masked pixels will not be considered. You would just need to remember to invert the mask in the settings, so that all pixels *outside *the objects are retained.

Regards,
-Mark

Hi Michael,

In addition, FilterObjects needs some input to properly filter out objects. You didn’t say what measurement criteria you would use to exclude particular objects (size, shape, intensity, etc?). So you need at least one Measurement module upstream of FilterObjects, which you have set to filter out based simply on Object_Number which is really just an arbitrary number we assign each object. Once you measure features upstream of FilterObjects, other features will be available in the drop-downs.

If you want to remove objects manually, look at EditObjectsManually.

Cheers,
David

Mark,

This is working perfectly.

David, FilterObjects only seems to define objects, not allow you to discard them in a future analysis of the same image. Mask image is working pretty darn well so far.

Now I have to wrestle with getting cellprofiler to count spindle shaped cells, but that seems relatively easy, thus far.

Thanks for your help,

Michael

I seem to have hit another roadblock.

I’m trying to design a pipeline to identify the spindle shaped cells in the image above. I’ve tried the worm toolbox, with some success, but I still seem to be getting inconsistent counting of these spindle shaped cells.

I’ve considered two methods of counting these cells. First, I could stick with the cell profiler worm counting pipeline I’ve been adjusting. Second, I could train cellprofiler analyst to detect these cells.

What I’m asking is whether anyone has any advice as to which of these two methods to count these spindle-shaped cells would be the simplest. If the cellprofiler analyst option turns out to be the better choice, how would I go about setting up a properties file, object table, and training set? Is there a very beginner walkthrough for how to get started with cell-profiler analyst?

Better method to count fibrocytes and other spindle shaped cells can be found here: viewtopic.php?f=14&t=3923

Good catch; hopefully, that prior post is helpful.
-Mark