I’m currently in the process of messing around with QuPath, trying to quantify pulmonary granulomas in a less painful and more objective way than manually counting them, as everyone seems to do in my lab.
So far I’ve been tweaking cell detection settings and analysis’ to better classify cells automatically. In the very specific granuloma model i’m using I’ve almost got it down so that 90-95% of detections are cells belonging to the aforementioned granulomas.
I have a few questions though, I appreciate any help with answering them and apologise in advance if they’ve been asked before. I couldn’t really find much information anywhere which is surprising given how good QuPath is.
Is there a way to exclude cells from being detected as a class if they are not adjacent to a certain number of cells of the same characteristic?
Is there a way to export object classifiers? I don’t believe there is, although I’m fairly sure I can use a training image for this, although I haven’t actually tried or read too much about this yet. I’m also quite fond of having a classifier i could use across multiple projects involving similar samples.
Would there be a way to standardise staining vectors between samples? I found two sets in a series of slides that I had misplaced and I’m intending to stain them, I’m considering trying to standardise them based off of a mean stain intensity between both batches of slides, would this work?
All of my slides contain heart tissue and some of them contain intensely stained, folded regions. Is there a way for me to exclude high stain intensities from classification by the object classifier?
I’m currently using the normal object classifier labelled as “train object classifier”. I’m quite interested in the pixel classifier but outside of a single youtube video and a descriptive paragraph, I’m not sure how to use it. Does anyone know of a resource on it?
Thanks again for your help, and thanks to everyone who helped to develop this software.