Hi Jane
To apply a "Matched Filter" to a 3D matrix, design a matched filter that corresponds to the pattern you wish to detect, such as a 'Gaussian filter'. Apply this filter to the 3D matrix using 3D convolution to enhance the desired features.
Here's the MATLAB code for this process:
image3D = rand(200, 200, 1024); % Replace with your actual data
% Design the matched filter (example: Gaussian filter)
filterSize = [5, 5, 5]; % Size of the filter
sigma = 1; % Standard deviation for Gaussian
h = fspecial3('gaussian', filterSize, sigma);
% Apply the matched filter using 3D convolution
filteredImage3D = convn(image3D, h, 'same');
% Visualize or further process the filtered image
sliceNumber = 512; % Choose a slice index to visualize
imshow(filteredImage3D(:,:,sliceNumber), []);
title(['Filtered Slice at Z = ', num2str(sliceNumber)]);
Please refer to the below MathWorks documentation links:
Hope this helps!
