CODEWITHSUNDEEP
arraysmatlabmultidimensional-array4d
machinery
machinery

Reputation: 6290

4D matrix operations in Matlab

I have a set of 4D matrices in Matlab. The first three dimensions are spatial, the last is temporal. That means each voxel is a time series. If Img is the 4D image, Img(x,y,z,:) is the time series of voxel with coordinate (x,y,z).

Now I want to normalize (zero mean and unit variance) each time series of the image. How can I do this? Perhaps with zscore(Img,[],4)?

Second, I want to concatenate the time series of all images. Let's say Img1, Img2, Img3,....Imgn are the 4D images. For each voxel I want to concatenate the time series over all images so that in the end I have one 4D image with the same spatial but extended temporal dimension. So let's say the voxel has the coordinate (x,y,z), then the concatenated time series would be [squeeze(Img1(x,y,z,:)); squeeze(Img2(x,y,z,:));....;squeeze(Imgn(x,y,z,:))]. This should be done for all voxels.

How can I do this? It could be done with for loops but this is not efficient.

Upvotes: 2

Views: 592

Answers (1)

Luis Mendo
Luis Mendo

Reputation: 112759

First question: normalize

This can be easily done with bsxfun:

Img = bsxfun(@rdivide, Img, std(Img,0,4)); %// unit variance. Or change 0 to 1; see std
Img = bsxfun(@minus, Img, mean(Img,4)); %// zero mean

Second question: concatenate

Just use cat along the fourth dimension:

result = cat(4, Img1, Img2, Img3);

It's easier if you have all images in a cell array:

cellImgs = {Img1, Img2, Img3};

because then you can use a comma-separated list

result = cat(4, cellImgs{:});

so the code is independent of the number of images.

Upvotes: 5

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