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On 5/10/2010 3:09 PM, subrajeet Mohapatra wrote:
> I want to create subimages from a single image which contains many WBC
> cells. I am using regionprop and bounding box it is creating many
> unwanted subimages also. I have tried convexhull also same problem
> persists. Any way to reduce small unwanted subimages.
>
> the below link contains the image
> http://www.healthsystem.virginia.edu/internet/hematology/images/Acute-lymphoblastic-leukemia-L1-subtype-100x-website.jpg
>
you could get rid of small areas by smoothing the image before. however
than also adjacent cells would be melted and could be differentiated
enough. a mixture of smoothing, adaptive thresholds (including the
laplacian, etc. ) and a threshold on number of pixels in resulting area
can help. however under different conditions the parameters of the
algorithm like the thresholds will have to be adapted.
I crafted an example for you, that might act as an inspiration. However
this is a whole search area with many possible approaches. This is only
the easiest one.
Jan
function [subs] = SimpleRegionSelection()
% Divides images of many cells in single images of cells using some simple
% smoothing and threshold criteria. Works only on good-enough pictures and
% may require tweaking.
%
% Jan Keller (jkeller1@gwdg.de)
[image, colmap] =
imread('Acute-lymphoblastic-leukemia-L1-subtype-100x-website.jpg'); %
three frames (r,g,b) I believe
% parameters
smoothing_size = 10; % smoothing gaussian diameter in pixel
threshold = .18; % intensity treshold relative to maximum
numpixel_threshold = 5000; % number of pixel threshold in each area
img = double(image);
img = sqrt(img); % this is a trick to reduce the influence of image
noise on the whole algorithm
% first step some smoothing (3 pixels wide)
l = round(2 * smoothing_size);
[x, y] = ndgrid(-l:l, -l:l);
smoothing_kernel = power(2., -(x.^2+y.^2) / (smoothing_size/2)^2);
smoothed = zeros(size(img));
for ki = 1 : size(img, 3)
smoothed(:, :, ki) = imfilter(img(:, :, ki), smoothing_kernel, 'same');
end
% add all three color channels up and normalize and make negative because
% original image is white outside of cells
smoothed = sum(smoothed, 3);
smoothed = 1. - smoothed ./ max(smoothed(:));
% thresholding and get regions
bw = smoothed > threshold;
[label, n] = bwlabel(bw);
% separate to subs
subs = {};
for ki = 2 : n % ignoring the first, its the background
% get values of coordinates in regions
maskpos = find(label == ki);
[x, y] = ind2sub(size(label), maskpos);
% obtain bounding box with some border
border = 5;
xmin = max(min(x) - border, 1);
xmax = min(max(x) + border, size(label, 1));
ymin = max(min(y) - border, 1);
ymax = min(max(y) + border, size(label, 2));
chunk = image(xmin:xmax,ymin:ymax,:);
numpixel = size(chunk, 1) * size(chunk, 2);
fprintf('%d\n', numpixel);
if numpixel > numpixel_threshold
% write to cell array
subs = [subs, {}];
end
end
% this is just for visualisztion
figure;
imagesc(label);
title('image mask');
for ki = 1 : length(subs)
figure;
imagesc(subs{ki});
colormap(colmap);
s = sprintf('subimage %d', ki);
title(s);
end
end
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