http://imagej.273.s1.nabble.com/declump-those-buggers-tp3685220p3685223.html
> Dear all,
>
> thanks a lot for all your suggestions and comments. I will work with them as
> soon as possible (at the moment I am packed with teaching and examination
> duties).
>
> I am happy to see that my post has not only stimulated some 'image analysis'
> discussions, but also some very basic scientifc ones. Now, to prevent
> misunderstandings: I do not only want to count cells. There are much easier
> ways to do this, even with ImageJ (I would just determine the area covered
> by DAPI-stained 'things' and divide that by an average nucleus area). I will
> attach cropped images of what I would eventually like to get at. For all the
> subsequent analysis steps it is mandatory to faithfully segment indivdual
> cells. It may even be necessary to determine the degree of clumping, as this
> also carries biological information.
> We are working with cultures of neural stem cells, which, unfortunately are
> somewhat heterogeneous. We fix and stain them with various antibodies after
> whatever treatment. The question now is: what percentage of cells shows what
> level of staining for a particular marker? For a start I wanted to use
> nuclear stains, e.g. antibodies against transcriptions factors. Some cells
> will have a lot, others less. E.g. it will be interesting to determine which
> and how many of the proliferating cells, identified by an antibody against a
> proliferation marker, express transcription factor x. Combining various
> antibodies will then help to characterize the cells with respect to
> treatment. Think of it like a FACS-experiment, the difference being that the
> cells are not in suspension (this by the way could be achieved, but would
> require the cells to be dissociated, which not always is a good way to go
> about). So for each cell in the image there should be a 'number' for its
> staining intensity for 'label1', 'label2', and possibly more (depending on
> the number of labels one can apply). The basis for all this is to faithfully
> identify and segment all (or most) cells in the picture. Behind all of this
> obviously is an attempt to do this somewhat objectively, not making it
> necessary to put cohorts of students at work to count all of this manually,
> or better put 'eye'ly. Of course it will be necessary to analyze a lot of
> images in batch mode, ideally unsupervised (some moderate
>
http://imagej.588099.n2.nabble.com/file/n6201542/RGB.jpg editing could be
> bearable at the end). If one would do a biochemical expriment, one would
> homogenize the cells, make a Western-Blot, normalize it to the number of
> cells and so on. In this way, however, information about single cells in a
> heterogeneous population would be lost all together.
> In a next step of the analysis, we would like to include cytoplasmic markers
> as well, which then will make the whole business of doing all this on a
> single cell level even more demanding. But that's the direction, where a lot
> of commercial (and unaffordable) attempts are aimed at (see e.g. the
> Definiens software).
> A useful addition in this context would be an interactive way of combining
> graphs of combinations of measurement with the images themselves: e.g.
> display a scatter blot of size vs. intensity and be able to click on a point
> in the graph and see the corresponding cell in the image and vice versa. In
> addition, doing somewhat like gating in FACS would be more than helpful.
> All these wishes by far exceed my cababilities of constructing routines for
> ImageJ, which is why I am asking advice rom the vast community of 'cracks'.
>
> This much for today. I will be happy to answer more questions and will
> certainly wellcome any suggestions. I will attach a picture with altogether
> three labels (dapi in the blue channel). Quality is limited as I can only
> uoload jpegs.
>
> Cheers
> Matthias
> -
>
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