Hi Reet,
To efficiently compute the correlation coefficients, we will shift the data along each direction and compute the correlation between the original and shifted data.
Here’s MATLAB code snippet to illustrate using ‘corrcoef’ function for data-matrix:
Step 1: Read the 3D image
% For demonstration, we will generate a random 3D matrix
Nx = 100; Ny = 100; Nz = 10; % Replace with actual dimensions
img3D = rand(Nx, Ny, Nz); % Replace with actual image data
sizeOfImage = size(img3D)
Step 2: Calculate correlation coefficients
% For x-direction
x_original = img3D(1:end-1, :, :);
x_shifted = img3D(2:end, :, :);
x_original_flat = x_original(:);
x_shifted_flat = x_shifted(:);
corr_x = corrcoef(x_original_flat, x_shifted_flat);
corr_x = corr_x(1, 2) % Get the correlation coefficient
% For y-direction
y_original = img3D(:, 1:end-1, :);
y_shifted = img3D(:, 2:end, :);
y_original_flat = y_original(:);
y_shifted_flat = y_shifted(:);
corr_y = corrcoef(y_original_flat, y_shifted_flat);
corr_y = corr_y(1, 2)
% For z-direction
z_original = img3D(:, :, 1:end-1);
z_shifted = img3D(:, :, 2:end);
z_original_flat = z_original(:);
z_shifted_flat = z_shifted(:);
corr_z = corrcoef(z_original_flat, z_shifted_flat);
corr_z = corr_z(1, 2)
Step 3: Display the results
fprintf('Correlation coefficient in x direction: %f\n', corr_x);
fprintf('Correlation coefficient in y direction: %f\n', corr_y);
fprintf('Correlation coefficient in z direction: %f\n', corr_z);
For more details on the Correlation coefficients, go through the following MathWorks documentation.
