MRI Slice image reconstruction

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Roshtha
Roshtha on 17 Mar 2016
Answered: FELIPE COSTA on 26 Nov 2019
Hello all,
I have an MRI K-Space data 320 x 320 x 256 x 8 (4D complex double) from < mridata.org > . The data represents 320 x 320 K-Space of 256 slices from 8 channels. I am trying to reconstruct images for each slice. Here is the matlab code I tried:
% Version - 1
kspacedata= kspacefile.kdata;
imRef = ifftshift(ifftn(kspacedata));
imSOS = squeeze(sqrt(sum( abs(imRef).^2, 4))); % sum-of-squares to combine all channels
% Version - 2
kspaceSlicedata = kspacedata(:,:,100,:);
imSliceRef = ifftshift(ifftn(kspaceSlicedata));
imSliceSOS = squeeze(sqrt(sum(abs(imSliceRef).^2, 4))); % sum-of-squares to combine all channels
% Plotting
figure;
subplot(1,2,1); imagesc(imSOS(:,:,100));title('Version - 1');axis image; colormap(gray);
subplot(1,2,2); imagesc(imSliceSOS);title('Version - 2');axis image; colormap(gray);
In Version - 1, I take inverse transform on entire kspace data and plot image data corresponding to slice 100. In Version - 2, I take kspace data corresponding to slice 100 and do inverse transform on this kspace and plot the image data. Here is the output images I obtained.
I thought both versions will reconstruct the same way. But images appeared different. How can I take kspace data corresponding to one slice and perform inverse transform to reconstruct slice image?
Thanks.

Accepted Answer

zoey yang
zoey yang on 21 Sep 2017
the version 1 is 3D FFT, and version 2 is 2D FFT. It is about the way you acquired data. version 1: encode the entire 3D space and acquire the data to fill the k space. version 2: encode the slice and acquire the slice data then you encode the next slice and acquire data. That's the difference.

More Answers (2)

Whae five
Whae five on 21 May 2017
https://www.mathworks.com/help/images/examples/exploring-slices-from-a-3-dimensional-mri-data-set.html

FELIPE COSTA
FELIPE COSTA on 26 Nov 2019
I tested here with another dataset and I was having the same problem. The function ifftn can be used for 3 or more dimensions. So it worked in your first version. Your second version is a 2D, so you must use ifft2 instead.

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