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Positive cell detection isn’t necessary. It’s only a simple version of the classifier, which can make positive cells either above or below a threshold. Likewise, if you have access to the channel during Positive Cell Detection, you can use that as a threshold to figure out which cells are Positive (Negative). The class name doesn’t mean anything. You can use your “Negative” cells as the positive cells. The only limitation is you couldn’t do a +1 +2 +3 tier if you use Positive cell detection that way.

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Would you have any ideas about how I could define the ROI with the fluorescent channel and count cells in the brightfield channel? Thanks in advance!

Just to emphasize, this is not specific as far as a file type. Brightfield images can be one, three or other channel images. And saved in a variety of ways.

Thanks for your reply! Sadly, I wasn’t able to figure things out. It only got more confusing since my measurement method was wrong. I am trying to work on Chris’ solution right now, by converting my DAPI channel to greyscale. However, it would be most ideal to work this out without transforming the image. I am very new to image processing, so I will google and try out the things you have suggested!

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If it’s really a DAPI channel, it is already grayscale. The color doesn’t mean anything. If it has been resaved as an RGB image, that’s different. It isn’t yet clear what you are working with, what you are doing, or what you are getting.

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The problem starts when I load the images in QuPath: it is auto detected as fluorescent. If I try to change type, I can only select other or unspecified. I do not even have a brightfield option! Hence, I can not use positive cell detection, as the thresholds Cell Max and Cell Mean are both for bright pixels, whereas, my staining is dark.

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This document discusses methods for calculating illumination levels in indoor spaces. It describes the lumen method, which uses calculations involving flux, illumination levels, room dimensions, and reflectance values to determine lighting requirements. It also covers utilization factors, maintenance factors, glare indices, and considerations for lighting layout and control of glare. The goal is to provide uniform illumination while avoiding discomfort glare through analytical lighting design methods.Read less

Here’s what I am trying to do: I have .czi images (a bioformat directly from the microscope) with one greyscale brightfield channel (with BCIP/NBT staining) and a fluorescent channel with DAPI, to label the nuclei. Hence, one channel was obtained in a fluorescent channel, while the other was acquired in a brightfield channel.

Ah, did you get things figured out then? There is a measurement checkbox for standard cell detection, and measurement functions for things like CellPose and StarDist. Alternatively for most objects you can use Add Features to add more measurements based on other channels.

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I would like to count the number of cells that are stained with BCIP/NBT (dark blue staining, brightfield). Thus, I need to detect cells and annotate the ROI using the DAPI channel and count them using the brightfield channel.

I have .czi images (multichannel) with one greyscale brightfield channel (with BCIP/NBT staining) and I have a fluorescent channel with DAPI, to label the nuclei. I would like to count the number of cells that are stained with BCIP/NBT. Hence, I need to detect cells and annotate the ROI using the fluorescent channel and count them using the brightfield channel.

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A fluorescent image means qupath is looking for bright pixels against a dark background, a brightfield image means qupath is looking for dark pixels against a dark background. If you set your image to either of these, the results for the other will not make sense unless your brighfield is inverted to have a dark background.