problem with image brain tumor image processing

Question

redroses 2019-12-1

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/494147-problem-with-image-brain-tumor-image-processing

评论： Image Analyst 2019-12-2

Hi everyone, I have to do tumor brain segmentation for this picture. The lesion is located at the upper right of the brain. I'm currently having difficulties in removing the background as the colour of the background is similar to the other parts of the brain too. Can someone help me with the coding? thank you so much

the final outcome should be like this:

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KALYAN ACHARJYA 2019-12-1

编辑：KALYAN ACHARJYA 2019-12-1

在 MATLAB Online 中打开

May be these steps works:

Histeq>>Edge Detection>>Morpho/blob detection

If this works then the coding implementation is easy, hope you can do that.

redroses 2019-12-1

thanks sir.

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Answer 1

Image Analyst 2019-12-1

3
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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/494147-problem-with-image-brain-tumor-image-processing#answer_404133

See my skull stripping demo. It does that.

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Image Analyst 2019-12-1

在 MATLAB Online 中打开

What do you mean "submit"? Are you going to submit my code as your own? Assuming not, try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures if you have the Image Processing Toolbox.
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 22;
% 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 color demo image.
folder = pwd;
baseFileName = 'image.jpeg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % 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.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(grayImage);
if numberOfColorBands > 1
	fprintf('This image is RGB.  I will change it to gray scale.\n');
	grayImage = grayImage(:, :, 2);
end
% Display the original image.
subplot(2, 2, 1);
imshow(grayImage);
axis('on', 'image');
title('Green Channel Image', 'FontSize', fontSize);
impixelinfo;
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0.1, 1, 0.9]);
subplot(2, 2, 2);
imhist(grayImage);
grid on;
title('Intensity Histogram', 'FontSize', fontSize);
% It's gray scale.  Threshold to create a binary image.
binaryImage = grayImage > 35 & grayImage < 55; % or whatever value works.
subplot(2, 2, 3);
imshow(binaryImage, []);
axis('on', 'image');
title('Binary Image', 'FontSize', fontSize);
% Get rid of partial blobs leaving the field of view.
binaryImage = imclearborder(binaryImage);
% Get rid of blobs less than 500 in area.
binaryImage = bwareaopen(binaryImage, 500);
binaryImage = imfill(binaryImage, 'holes');
% Label the image so we can get rid of the dark region near the skull
[labeledImage, numberOfblobs] = bwlabel(binaryImage);
% Remove outer one
binaryImage = ismember(labeledImage, [2:numberOfblobs]);
% Take the largest blob only.
binaryImage = bwareafilt(binaryImage, 1);
% Relabel now.
[labeledImage, numberOfblobs] = bwlabel(binaryImage);
% Apply a variety of pseudo-colors to the regions.
coloredLabelsImage = label2rgb (labeledImage, 'hsv', 'k', 'shuffle');
% Display the pseudo-colored image.
subplot(2, 2, 4);
imshow(coloredLabelsImage);
axis('on', 'image');
title('Filled Binary Image', 'FontSize', fontSize);
% Make measurements of area.
props = regionprops(binaryImage, 'Area', 'Centroid', 'MajorAxisLength', 'MinorAxisLength')
allAreas = [props.Area]
majorAxisLength = [props.MajorAxisLength]
minorAxisLength = [props.MinorAxisLength]

redroses 2019-12-2

i want to ask you a very last question, sorry for asking a lot. Dear image analyst, how did you read "grayImage > 35 & grayImage < 55; " this value from the historam ya?