Please send me the codes to remove the patient's name,date etc from the image.

I have sent you a ".m" file. In that ".m" file have made some comments seeking your help,please take a look at that. And please send the final code of that ".m" file and suggestions to improve it. Looking forward to you. See this is the ".m" file I was talking about. it is named "braintumor.m".

Answer 1

[Image Analyst]

Try this:

function test1
clc;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;

% 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 gray scale demo image.
folder = 'D:\temporary stuff';
baseFileName = 'brain_cancer2.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 = imread(fullFileName);
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage);
if numberOfColorBands > 1
  % It's not really gray scale like we expected - it's color.
  % Convert it to gray scale by taking only the green channel.
  grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the original gray scale image.
subplot(2, 3, 1);
imshow(grayImage, []);
axis on;
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 to Threshold Document', 'NumberTitle', 'Off') 

% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(grayImage);
subplot(2, 3, 2); 
bar(grayLevels, pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.

% Binarize the image
binaryImage = grayImage > 70;
% Display the image.
subplot(2, 3, 3);
imshow(binaryImage, []);
axis on;
title('Initial Binary image', 'FontSize', fontSize);

% Get the skull only
binaryImage = imfill(binaryImage, 'holes');
% Get a binary image with only the largest blob:
binaryImage = ExtractNLargestBlobs(binaryImage, 1);
% Display the image.
subplot(2, 3, 4);
imshow(binaryImage, []);
axis on;
title('Skull Only', 'FontSize', fontSize);

% Smooth the skull mask a bit by getting the convexhull.
% Another option would be to use activecontour()
mask = bwconvhull(binaryImage);
% Get the masked image
maskedImage = grayImage; % Initialize
maskedImage(~mask) = 0; % Blacken outside skull
% Display the image.
subplot(2, 3, 5);
imshow(maskedImage, []);
axis on;
title('Masked Image', 'FontSize', fontSize);

%==============================================================================================
% Function to return the specified number of largest or smallest blobs in a binary image.
% If numberToExtract > 0 it returns the numberToExtract largest blobs.
% If numberToExtract < 0 it returns the numberToExtract smallest blobs.
% Example: return a binary image with only the largest blob:
%   binaryImage = ExtractNLargestBlobs(binaryImage, 1);
% Example: return a binary image with the 3 smallest blobs:
%   binaryImage = ExtractNLargestBlobs(binaryImage, -3);
function binaryImage = ExtractNLargestBlobs(binaryImage, numberToExtract)
try
  % Get all the blob properties.  Can only pass in originalImage in version R2008a and later.
  [labeledImage, numberOfBlobs] = bwlabel(binaryImage);
  blobMeasurements = regionprops(labeledImage, 'area');
  % Get all the areas
  allAreas = [blobMeasurements.Area];
  if numberToExtract > length(allAreas);
    % Limit the number they can get to the number that are there/available.
    numberToExtract = length(allAreas);
  end
  if numberToExtract > 0
    % For positive numbers, sort in order of largest to smallest.
    % Sort them.
    [sortedAreas, sortIndexes] = sort(allAreas, 'descend');
  elseif numberToExtract < 0
    % For negative numbers, sort in order of smallest to largest.
    % Sort them.
    [sortedAreas, sortIndexes] = sort(allAreas, 'ascend');
    % Need to negate numberToExtract so we can use it in sortIndexes later.
    numberToExtract = -numberToExtract;
  else
    % numberToExtract = 0.  Shouldn't happen.  Return no blobs.
    binaryImage = false(size(binaryImage));
    return;
  end
  % Extract the "numberToExtract" largest blob(a)s using ismember().
  biggestBlob = ismember(labeledImage, sortIndexes(1:numberToExtract));
  % Convert from integer labeled image into binary (logical) image.
  binaryImage = biggestBlob > 0;
catch ME
  errorMessage = sprintf('Error in function ExtractNLargestBlobs().\n\nError Message:\n%s', ME.message);
  fprintf(1, '%s\n', errorMessage);
  uiwait(warndlg(errorMessage));
end

%