Hello, I am trying to analyze a tissue that is predominantly composed of proteins instead of cells. This makes it difficult to use nuclei-based cell segmentation, so I’ve been using Ilastik pixel classification to differentiate my tissue from the background. However, I’m running into problems when I use the generated probabilities in CellProfiler to identify primary objects (i.e. tissue). It identifies uneven lumps of pixels as an object, and using smaller pixel numbers as boundaries isn’t working because it just excludes the larger areas that are still tissue. The same problem still occurs when I do the object classification with Ilastik as well.
As a solution, I was wondering if it’s possible to use the actual pixel classification as the segmentation mask for downstream analysis? Is there a way to use individual pixels or a set amount of pixels as my segmentation? Any help would be appreciated! Thanks.