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Creating binary 3D mask from MR volume

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banikr on 26 Apr 2020
Answered: banikr on 29 Apr 2020
Hello All,
I am trying to create a 3D binary mask for MR head volume. The image has 0 intensity for background and the tissue inside the image has integers. Morphological operations provide me very noisy output.
This is after bwconncomp, thresholding and imerode options.
Are there better ways to get volumetric masks?
Image Analyst
Image Analyst on 27 Apr 2020
I don't think the noise on the mask is the issue. Why did your classification routine quit classifying stuff below that line other than the blue stuff? For some reason, you have a mask that just quits below that line, and that has nothing to do with little noisy blips on it.
banikr on 27 Apr 2020
Yeah you are right, the noise has nothing to do with the classification.
The classification comes from CT image which only exists for the segmented section. Now for MR images there is no specific intensity scaling mechanism like CT. For my experiment, I also need the inferior section of the head labelled in MR space.
CT image was registered on MR space.

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Answers (2)

Mrutyunjaya Hiremath
Mrutyunjaya Hiremath on 27 Apr 2020
Hello banikr,
I think this is what you want ... if I am not wrong.
load mri;
% load mriVolume; %3D MRI data with data variable name 'mriVolume'
mriVolume = D;
% Assuming background pixels are 0
bwMask = false(size(mriVolume));
pixIndex = find(mriVolume > 0);
bwMask(pixIndex) = 1;
Mrutyunjaya Hiremath
Mrutyunjaya Hiremath on 27 Apr 2020
@ banikr,
ok got it, if MRI data is possible to share, please share. love to work on it.

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banikr on 29 Apr 2020
I just wanted to update the finding I have(following mask image).
I used the intensity 10 for thresholding and removed objects with area under 1000.
bi = (mr>10);
% volumeViewer(bi);
stat = regionprops(bi, 'Area', 'PixelIdxList');
for nn=1:length(stat)
s = stat(nn);
if s.Area<1000
end % remove small objects
bi = zeros(sz);
bi(s.PixelIdxList) = 1;
I tried to explain the value 10.
J = mr(mr~=0);
>> SkinMusclePrc = prctile(J,[20, 100], 'all')
SkinMusclePrc =
2×1 int16 column vector
The value 10 is on 20 percentile of the distribution.
let me know if that helps your search also.

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