MATLAB: How to extract thorax from CT scan image using largest connected components

thorax extraction

Largest connected component is used in thorax extraction after binarize image.then appling 2D hole filling algorithm

Best Answer

See my attached demo to extract the largest or smallest N blobs in a binary image.

Related Solutions

MATLAB: How can i separate all the connected regions in a binary image and display them individually.

Use bwlabel() and ismember

[labeledImage, numRegions] = bwlabel(binaryImage);
props = regionprops(labeledImage, 'Area')
% Compute all the areas.
allAreas = [props.Area]
% Display each blob in its own figure.
for k = 1 : numRegions
    thisRegion = ismember(labeledImage, k);
    figure;
    imshow(thisRegion);
    drawnow;
end

MATLAB: Largest connected component(circular)

Ibw = imfill(imread('coins.png')>100,'holes'); %example binary image
CC = bwconncomp(Ibw); %connected components
Objsz = cellfun(@numel,CC.PixelIdxList);  %size of blobs
[garbage, ObjszOrder] = sort(Objsz,'descend'); %descended sorting
stats = regionprops(CC,'stuff you need to write');
for ii = 1:length(ObjszOrder)
  if(iscircularenough(stats(ii)))
      %object ii wins!
      break
  end
end

I've done most of the work for you here. You have to determine what criteria you want to use to test circularity and what you need to extract from regionprops for this. The most common measurement of circularity is perimeter to area. Use wikipedia or the explanation of 'regionprops:equivdiameter' for the correct equation.

Best Answer

Related Solutions

MATLAB: How can i separate all the connected regions in a binary image and display them individually.

MATLAB: Largest connected component(circular)

Related Question