How can I identify number of cells in this image?
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I would like to count the number of cells in this image.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/545917/image.png)
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Star Strider
2021-3-11
Maybe I’m missing something in your objection to using those example, however this actually appears to work, even with the clusters. It’s not perfect (I douibt if it ever could be), however it appears to me to be acceptably close:
I = imread('AAS image.png');
[T,EM] = graythresh(I);
BW = imbinarize(I,0.4);
[Ctrs,Radi] = imfindcircles(BW(:,:,1), [9 20],'ObjectPolarity','dark', 'Sensitivity',0.925);
figure
imshow(I)
hold on
h = viscircles(Ctrs,Radi);
hold off
title(sprintf('Showing %d Detected Cells',numel(Radi)))
producing:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/545962/image.png)
.
3 个评论
Star Strider
2021-3-11
As always, my pleasure!
I can’t think of any way to get rid of the dark dots, other than possibly thresholding them. (I didn’t explore that.) To get an idea of what their magnitudes are, this could help:
figure
surf(I(:,:,1), 'EdgeColor','none')
grid on
colormap(jet(255))
colorbar
Rotate that in the figure GUI to examine it more closely. I’m not certain that it would be straightforward to eliminate them, however.
Mohammad Sami
2021-3-11
One way can be to use the built in matlab apps like color thresholder to figure out the thresholds you need.
更多回答(1 个)
Image Analyst
2021-3-11
I would first just threshold to exclude the background produce a binary image, and then label the blobs. Then identify blobs which are just single blobs - not touching others. Then get the average area of those. Then sum the binary image and divide by the average area. It should be reasonably accurate, expecially considering the count will vary a lot as the field of view moved or cells enter and leave the field of view. See my Image Segmentation Tutorial in my File Exchange for a demo.
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