Skull striping without affecting tumor region

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Sehrish
Sehrish am 5 Jul. 2012
Kommentiert: elif yoldas am 15 Apr. 2016
Can anyone help me to remove the skull part of the brain image without effecting the tumor region? the image is http://imageshack.us/photo/my-images/196/img6oe.jpg/ Actually the intensity level of tumor as well as the skull part is really high and whatever i tried, it effects the tumor region as well. kindly help me regarding this:

Antworten (3)

Matt Kindig
Matt Kindig am 5 Jul. 2012
Bearbeitet: Matt Kindig am 5 Jul. 2012
If you have the Image Processing Toolbox, you can use 'regionprops' to identify the various objects after your thresholding. For your particular image, I was able to identify the tumor using the following approach:
img = imread('/path/to/your/filename.jpg');
bw = (img > 0.5*255); %thresholded to remove background and white/gray matter
lbl = bwlabel(bw); %labelled regions
props = regionprops(lbl, 'Solidity', 'Area');
% solidity is the percentage "filled" of an area. For the skull,
%the solidity will be really low.
solidity = [props.Solidity];
area = [ props.Area];
hiSolid= solidity > 0.2; %get only high solidity objects
maxArea = max( area(hiSolid));
tumorLabel = find( area==maxArea); %label of tumor
tumor = ismember(lbl, tumorLabel); %b/w image of tumor
imshow(tumor); %this isolates tumor
  3 Kommentare
Sehrish
Sehrish am 5 Jul. 2012
its working but giving different results for different images. the problem is in threshhold values. How can i get automated threshholds?

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Felix
Felix am 5 Jul. 2012
Bearbeitet: Felix am 5 Jul. 2012
Unless you have a huge number of images, I think the best solution is to mask it manually, because no algorithm is as good as the eye. For example I use the program MIPAV, which can read many different scanner formats.

Anton Semechko
Anton Semechko am 5 Jul. 2012
Bearbeitet: Anton Semechko am 5 Jul. 2012
The simplest way to segment the tumor in the sample image would be to use region growing algorithm. There are a few implementations of this method on FEX, but for the following demo I used this one:
1) Download the function titled 'regiongrowing' from the link given above into your working directory.
2) Segment the tumor using pixel position [380 480] as the seed point:
% get the sample image
im=imread('http://desmond.imageshack.us/Himg196/scaled.php?server=196&filename=img6oe.jpg&res=landing');
% segment the ROI
thr=15; % intensity similarity tolerance
bw=regiongrowing(double(im),380,480,thr);
% fill in the holes
bw=imfill(bw,'holes');
% visualize the segmentation
r=im; g=im; b=im;
r(bw)=255; g(bw)=255;
rgb=cat(3,r,g,b);
figure, imshow(rgb)
clear r g b
You will get different results depending on the value of 'thr' parameter.
Hope this helps.
  9 Kommentare
elif yoldas
elif yoldas am 15 Apr. 2016
code is not done work and image is not found :(

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