MATLAB: How to calculate Euclidean distance in a 3D matrix

Question

I am trying to calculate the distance between a 2D point (though represented in 3D) and all the other 2D points in a 3D matrix, in order to determine which point in the matrix is closest to the individual. I prefer to use loops as little as possible.

Here's some example code:

vector = ones(1, 1, 2);
matrix1 = magic(3);
matrix2 = magic(3);
%matrix1 is the x coord, matrix 2 the y coord
matrix = cat(3, matrix1, matrix2); 
%What I want it to do:
dists = norm(matrix-vector)  %Size of dists should be (3,3,1)
[i,j,k]=ind2sub(size(dists), find(dists==min(dists(:)))) 
%Should return coordinates of smallest Euc dist

I just found bsxfun which duplicates the vector to subtract from the matrix:

diff = bsxfun(@minus, matrix, vector);

But then I still don't know how to make the matrices do the proper Euclidean distances between their points.

This does it, but still seems rather circuitous:

calc1 = bsxfun(@minus, matrix, vector);
calc2 = calc1.^2;
calc3 = sum(calc2, 3);
calc4 = calc3.^(1/2);
[winI,winJ] = ind2sub(size(calc4), find(calc4==min(calc4(:))));

Answer 1

calc           = sqrt(sum(bsxfun(@minus, matrix, vector) .^ 2, 3));
[value, index] = min(calc(:));
[winI,winJ]    = ind2sub(size(calc), index);

This considers one minimal value only, if several are identical.