Identify the nonzero pixels

I have a stack of 3D volumes, i.e. 4D with dimensions [156, 192, 26, 41]. I have also a 3D binary mask with dimensions [152, 192, 26].

I would like to identify the locations of the nonzero pixels to speed up a calculation that I am doing in a for loop.

I tried the following but it returns a 1D array. I am looping over the voxels so it doesn't work. If I do that in the loop would it work? My results look totally black so I am not sure if it's the way I identify the nonzero pixels the problem or something else.

f = find(mask(:,:,:,1)>0);

for i=1:size(r,1)
       for j=1:size(r,2)
            for k=1:size(r,3)
                if (mask(i,j,k)>0)
                 do some calculations..
                end
            end
        end 
end 

[Image Analyst]

Not sure what you expect as an output. Would it be

1. A binary 4-D volume where your original 4-D volume is masked?
2. A list giving the indexes of the non-zero pixels in the mask?
3. The total number of non-zero pixels in the masked volume?

[Walter Roberson]

Is it possible for the values to be negative? Because you ask about finding non-zero pixels, but your code tests for > 0 .

[Gina Carts]

The mask is binary has values 0 and 1 only. I want to identify the nonzero pixels i.e. pixels=1.

[Image Analyst]

He's not asking about the mask of course. We know that masks have only 0 and 1. He's asking about the 4-D array that the mask is to be applied to.

Plus you didn't answer my question. Do you want 1, 2, or 3.

Answer 1

[Matt J]

Ideally, your code would have no more than one loop. It could look like the following,

locations=(mask>0);

for i=1:41
    
    A=volume_stack(:,:,:,i); %extract a 3D volume from stack
    
    B = A(locations); %extract its masked voxels
    
    A(locations) =  .... calculations with B ....;
    
    volume_stack(:,:,:,i)=A; %put back in the stack
    
end

Answer 2

[Walter Roberson]

idx = find(mask);
[r, c, p] = ind2sub(size(mask), idx);

Now mask(r(K), c(K), p(K)] is nonzero, and you can access

Your4DArray(r(K), c(K), p(K), :)

However, I notice that your 4D array has 156 rows but your mask has 152 rows, and I do not know how the mask matches the array.