take largest connected components in 2D slices and then reconstruct the 3D by stacking them
Hello, I am doing some morphological image processing. I want to remove the 4 unwanted blobs from the binary object(image below) If I axially slice the image, I can take the largest connected component and exclude others like the image below: I have tried the following codes which results binary size mismatch issues. ind = 1; sz = size(bi) % bi is the 3D mask with dimension: 170x256x100 final_mask = zeros(sz) for i = 1:sz(3) %taking the 2D axial slice iterations-> 1:100 cc = bwconncomp(bi(:,:,i)); % disp(cc) S = regionprops(cc, 'Area', 'PixelIdxList');%'Centroid'); ax_slice = zeros(sz(1), sz(2)); numPixels = cellfun(@numel, cc.PixelIdxList); % disp(numPixels) [biggest,idx] = max(numPixels); % taking the largest component number of pixels and their indices ax_slice(cc.PixelIdxList{idx})= 1; final_mask(:,:,i) = ax_slice; end Please let me know how to deal with it.
Prashant Kumar answered .
2025-11-20
clc % clear command window cla % clear axes bi11 = bi; % create copy of 'bi' bi1 = bi(:,:,170:end); % get top part R = 2; % radius of structuring element [x,y,z] = meshgrid(-R:R); % X Y Z 3d matrices el = x.^2+y.^2+z.^2 <= R^2; % sphere of radius 'R' bi2 = imerode(bi1, el); % erode image bi3 = imdilate(bi2, el); % dilate image bi11(:,:,170:end) = bi3; % replace original top part isosurface(bi11,.95) % display 3d image axis vis3d light