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Although I am not new to math or programming, I am a total newbie to image segmentation. I have the following light microscope image

H&E Stail and I would like to segment it into cytoplasm (the magenta background) vs. the nuclei (the round-ish objects that look like cells). I am working in MATLAB.

I was hoping someone with segmentation or image processing experience could tell me what they thought would be an efficient approach.

First, do you see any issues with this image that I ought to pre-process out? E.g. non-uniform background illumination, noise, etc. I am not familiar with how to identify these things visually in an image.

Secondly, there are two dominant colors in this image, corresponding to two dyes (hematoxylin and eosin, or "H&E" for short). The cytoplasm and nuclei have different colors, which in principle we know the RGB values of. So I first tried a method of color deconvolution by Ruifrok to try to separate out the pink from the purple.

Once I did that, the cytoplasm and nuclei seem to have very different textures. I tried a range filter and got the result below:

enter image description here

Do you have any suggestions for where I can go from here? How can I eliminate the regions with cytoplasm and end up with clearly segmented nuclei?

I do not know much about graph cuts. Do you think they would be useful?

Please let me know if I need to clarify the question.

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People were approaching similar problems with methods deriving from Watersheds thresholding. Here, is a sample of Nuclei Seperation, and here is an OpenCV sample. You might try it out.

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  • $\begingroup$ Thanks! This is useful to know. I hadn't thought of using watershed-based methods here, because the nuclei are clear and contain nucleoli, so they aren't local extrema...maybe it's worth a quick try. $\endgroup$ – ccbb Feb 24 '16 at 19:53
  • $\begingroup$ It would be good if you share the results here so that people get an idea. $\endgroup$ – Tolga Birdal Feb 27 '16 at 15:07
  • $\begingroup$ Will do so...unfortunately have been a little busy right now with other things. :) I may try some kind of snakes type method first. $\endgroup$ – ccbb Mar 1 '16 at 14:41
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There an algorithm in CellProfiler. It's basic, but it may help you if you are a beginner. The algorithm separates the channels, applies a threshold to detect roughly the nuclei, then use the result to feed a watershed constrained.

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  • $\begingroup$ Thank you...this might be the color deconvolution algorithm by Ruifrok. This is a good suggestion. $\endgroup$ – ccbb Mar 1 '16 at 14:42
  • $\begingroup$ This algorithm might be used as a first step, but the end is thresholding+watershed. $\endgroup$ – FiReTiTi Mar 1 '16 at 18:24
  • $\begingroup$ Sorry I indeed just meant the first step $\endgroup$ – ccbb Mar 1 '16 at 20:02

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