watershed algorithm in matlab

旧街凉风 提交于 2019-11-28 23:55:50
Jonas

Here's one way to segment the image using watershed. There's plenty more you could do (e.g. fuse cells with two nuclei if they haven't completed cytokinesis yet), but the steps below should give you a first idea.

(1) Determine cell-background threshold, cell-nucleus threshold

%# read image
img = imread('http://i.stack.imgur.com/nFDkX.png');
%# normalize to 0...1
imgN = double(img-min(img(:)))/(max(img(:)-min(img(:))));
th1=graythresh(imgN);
th2 = graythresh(imgN(imgN>th1));

cellMsk = imgN>th1;
nucMsk = imgN>th2;

figure,imshow(cellMsk+nucMsk,[])

(2) Smooth the raw image (to avoid oversegmentation) and impose nuclei as minima

[xx,yy]=ndgrid(-5:5,-5:5);
gf = exp((-xx.^2-yy.^2)/20);
filtImg = conv2(imgN,gf,'same');

figure,imshow(filtImg,[])

filtImgM = imimposemin(-filtImg,nucMsk);

(3) Watershed, mask cells, and display

ws = watershed(filtImgM);
ws(~cellMsk) = 0;

lblImg = bwlabel(ws);

figure,imshow(label2rgb(lblImg,'jet','k','shuffle'));

(4) Now you can use REGIONPROPS on the labeled image to extract the statistics you want.

See watershed in the Image Processing toolbox and this post on cell segmentation on the 'Steve on Image Processing' blog.

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