MATLAB: How to extract the left and right lung regions from a CT Scan image

boundaryct imageedge detection

Hello, I've been trying to extract the left and right lung regions from this image using region labeling and various edge detection methods. The touble is that I am completely new to matlab and programming and have been completely unnsucessful. Any help would be greatly appreciated.

Thank you

http://i45.tinypic.com/11w3uds.jpg

Best Answer

There can be several approaches. How about something like this. You can try different values for thresholding, etc and look at the documentation of the functions to see what exactly they are doing.

%%Read image
img = imread('11w3uds.jpg');
%%Crop out unnecessary parts
cropped = img(90:400,40:460);
%%Threshold to isolate lung tissue
thresholded = cropped < 86;
%%Remove artifacts attached to border
clearThresh = imclearborder(thresholded);
%%Remove objects less than 40 pixels in size
imgBigTissue = bwareaopen(clearThresh,100);
imshow(imgBigTissue)

BWAREAOPEN

IMCLEARBORDER

All morphological operations in Image Processing Toolbox

Related Solutions

MATLAB: How to cut out an area that I’ve created a boundary to

Close. Here, try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
format longg;
format compact;
fontSize = 20;
% Change the current folder to the folder of this m-file.
if(~isdeployed)
  cd(fileparts(which(mfilename)));
end
  
% Check that user has the Image Processing Toolbox installed.
hasIPT = license('test', 'image_toolbox');
if ~hasIPT
  % User does not have the toolbox installed.
  message = sprintf('Sorry, but you do not seem to have the Image Processing Toolbox.\nDo you want to try to continue anyway?');
  reply = questdlg(message, 'Toolbox missing', 'Yes', 'No', 'Yes');
  if strcmpi(reply, 'No')
    % User said No, so exit.
    return;
  end
end
% Read in a demo image.
folder = 'C:\Users\Student\Documents\Temporary';
baseFileName = '2z3nja1.jpg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = rgb2gray(imread(fullFileName));
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);
% Display the original gray scale image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.

set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Give a name to the title bar.

set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') 
% Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(grayImage);
subplot(2, 2, 2); 
bar(pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Find border and mask it off
binaryImage = grayImage == 255;
% Display the image.



subplot(2, 2, 3);
imshow(binaryImage, []);
title('Original Binary Image', 'FontSize', fontSize);
% Get just hte border pixels.
borderImage = logical(binaryImage - imclearborder(binaryImage));
% Move the outer edge in a little bit.
borderImage = imdilate(borderImage, true(7));
% Display the image.
subplot(2, 2, 4);
imshow(borderImage, []);
title('Border Pixels Image', 'FontSize', fontSize);
% Start a new figure.
figure;
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Give a name to the title bar.
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') 
% Erase border pixels.
grayImage(borderImage) = 0;
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Masked Image', 'FontSize', fontSize);
% Threshold for dark pixels.
binaryImage3 = (grayImage > 0) & (grayImage < 125); % Threshold to isolate lung tissue
% Get the two largest blobs.
[labeledImage numberOfBlobs] = bwlabel(binaryImage3);
blobMeasurements = regionprops(labeledImage, 'Area');
allAreas = [blobMeasurements.Area];
[sortedAreas sortIndices] = sort(allAreas, 'descend');
% Get a list of the blobs that meet our criteria and we need to keep. 
keeperIndexes = [sortIndices(1), sortIndices(2)]; 
% Extract only those blobs that meet our criteria, and 
% eliminate those blobs that don't meet our criteria. 
% Note how we use ismember() to do this.
keeperBlobsImage = ismember(labeledImage, keeperIndexes); 
% Binarize and fill holes.
binaryImage3 = imfill(keeperBlobsImage>0, 'holes');
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage3, []);
title('Two Largest Regions', 'FontSize', fontSize);
% Re-label with only the keeper blobs kept.
labeledImage = bwlabel(keeperBlobsImage, 8);     % Label each blob so we can make measurements of it
% Find outer boundaries and trace over image.
% bwboundaries() returns a cell array, where each cell contains the row/column coordinates for an object in the image.
% Plot the borders of two largest regions returned by bwboundaries.
subplot(2, 2, 3); 
imshow(grayImage, []);
title('Outlines, from bwboundaries()', 'FontSize', fontSize);
hold on;
boundaries = bwboundaries(binaryImage3);  
numberOfBoundaries = size(boundaries);
for k = 1 : numberOfBoundaries
  thisBoundary = boundaries{k};
  plot(thisBoundary(:,2), thisBoundary(:,1), 'g', 'LineWidth', 2);
end
hold off;
% Now let's extract out just the lungs.
maskedImage = zeros(rows, columns, 'uint8'); % Initialize.
maskedImage(binaryImage3) = grayImage(binaryImage3);
subplot(2, 2, 4); 
imshow(maskedImage, []);
title('Lungs Masked', 'FontSize', fontSize);

MATLAB: How to segment trus prostate image

THere is nothing built in to do that so you'll have to search the literature to see if anyone has done that before. Try PubMed, or VisBib.

http://www.visionbib.com/bibliography/contentsmedical.html#Medical%20Applications,%20CAT,%20MRI,%20Ultrasound,%20Heart%20Models,%20Brain%20Models

Best Answer

Related Solutions

MATLAB: How to cut out an area that I’ve created a boundary to

MATLAB: How to segment trus prostate image

Related Question