segmentation by marking points around the region

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Elysi Cochin
Elysi Cochin on 17 Dec 2012
Commented: Image Analyst on 28 Jun 2018
please can someone help me with a sample code of medical image segmentation by the method of marking points around the region to be segmented..... i marked few points around the region but dont know how to proceed.... please could someone reply.....

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Accepted Answer

Image Analyst
Image Analyst on 17 Dec 2012
Use roipoly() or roipolyold() and then poly2mask().
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zainab srabony
zainab srabony on 28 Jun 2018
can anyone help me to find the function of mri brain image segmentation?

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More Answers (2)

Image Analyst
Image Analyst on 18 Dec 2012
See this demo:
% Demo to have the user freehand draw an irregular shape over
% a gray scale image, have it extract only that part to a new image,
% and to calculate the mean intensity value of the image within that shape.
% Also calculates the perimeter, centroid, and center of mass (weighted centroid).
% Change the current folder to the folder of this m-file.
if(~isdeployed)
cd(fileparts(which(mfilename)));
end
clc; % Clear command window.
clear; % Delete all variables.
close all; % Close all figure windows except those created by imtool.
imtool close all; % Close all figure windows created by imtool.
workspace; % Make sure the workspace panel is showing.
fontSize = 16;
% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'cameraman.tif';
% 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);
imshow(grayImage, []);
axis on;
title('Original Grayscale Image', 'FontSize', fontSize);
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
message = sprintf('Left click and hold to begin drawing.\nSimply lift the mouse button to finish');
uiwait(msgbox(message));
hFH = imfreehand();
% Create a binary image ("mask") from the ROI object.
binaryImage = hFH.createMask();
xy = hFH.getPosition;
% Now make it smaller so we can show more images.
subplot(2, 3, 1);
imshow(grayImage, []);
axis on;
drawnow;
title('Original Grayscale Image', 'FontSize', fontSize);
% Display the freehand mask.
subplot(2, 3, 2);
imshow(binaryImage);
axis on;
title('Binary mask of the region', 'FontSize', fontSize);
% Label the binary image and computer the centroid and center of mass.
labeledImage = bwlabel(binaryImage);
measurements = regionprops(binaryImage, grayImage, ...
'area', 'Centroid', 'WeightedCentroid', 'Perimeter');
area = measurements.Area
centroid = measurements.Centroid
centerOfMass = measurements.WeightedCentroid
perimeter = measurements.Perimeter
% Calculate the area, in pixels, that they drew.
numberOfPixels1 = sum(binaryImage(:))
% Another way to calculate it that takes fractional pixels into account.
numberOfPixels2 = bwarea(binaryImage)
% Get coordinates of the boundary of the freehand drawn region.
structBoundaries = bwboundaries(binaryImage);
xy=structBoundaries{1}; % Get n by 2 array of x,y coordinates.
x = xy(:, 2); % Columns.
y = xy(:, 1); % Rows.
subplot(2, 3, 1); % Plot over original image.
hold on; % Don't blow away the image.
plot(x, y, 'LineWidth', 2);
drawnow; % Force it to draw immediately.
% Burn line into image by setting it to 255 wherever the mask is true.
burnedImage = grayImage;
burnedImage(binaryImage) = 255;
% Display the image with the mask "burned in."
subplot(2, 3, 3);
imshow(burnedImage);
axis on;
caption = sprintf('New image with\nmask burned into image');
title(caption, 'FontSize', fontSize);
% Mask the image and display it.
% Will keep only the part of the image that's inside the mask, zero outside mask.
blackMaskedImage = grayImage;
blackMaskedImage(~binaryImage) = 0;
subplot(2, 3, 4);
imshow(blackMaskedImage);
axis on;
title('Masked Outside Region', 'FontSize', fontSize);
% Calculate the mean
meanGL = mean(blackMaskedImage(binaryImage));
% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1), centroid(2), 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1), centerOfMass(2), 'g+', 'MarkerSize', 20, 'LineWidth', 2);
% Now do the same but blacken inside the region.
insideMasked = grayImage;
insideMasked(binaryImage) = 0;
subplot(2, 3, 5);
imshow(insideMasked);
axis on;
title('Masked Inside Region', 'FontSize', fontSize);
% Now crop the image.
leftColumn = min(x);
rightColumn = max(x);
topLine = min(y);
bottomLine = max(y);
width = rightColumn - leftColumn + 1;
height = bottomLine - topLine + 1;
croppedImage = imcrop(blackMaskedImage, [leftColumn, topLine, width, height]);
% Display cropped image.
subplot(2, 3, 6);
imshow(croppedImage);
axis on;
title('Cropped Image', 'FontSize', fontSize);
% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1)-leftColumn, centroid(2)-topLine, 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1)-leftColumn, centerOfMass(2)-topLine, 'g+', 'MarkerSize', 20, 'LineWidth', 2);
% Report results.
message = sprintf('Mean value within drawn area = %.3f\nNumber of pixels = %d\nArea in pixels = %.2f\nperimeter = %.2f\nCentroid at (x,y) = (%.1f, %.1f)\nCenter of Mass at (x,y) = (%.1f, %.1f)\nRed crosshairs at centroid.\nGreen crosshairs at center of mass.', ...
meanGL, numberOfPixels1, numberOfPixels2, perimeter, ...
centroid(1), centroid(2), centerOfMass(1), centerOfMass(2));
msgbox(message);
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Aaron Smith
Aaron Smith on 13 Jul 2017
Edited: Aaron Smith on 13 Jul 2017
I did not set the size of my image. I know that it has 1024 rows as the image is x 1024 but I did not have a line of code like the one you detailed above. The code, spliced with yours and with the (rows, columns) line included looks like:
Folder = uigetdir('C:\Users\c13459232\Documents\MATLAB'); % selecta folder from which to select files
File = uigetfile(Folder); % select a file
Image = imread(File); % Read image
imshow(Image) % generate the image in a figure
again = true;
finalImage = false(rows, columns);
while again
thisRegion = roipoly;
% Add this in to the main one
finalImage = finalImage | thisRegion;
promptMessage = sprintf('Do you want to add another region?');
titleBarCaption = 'Continue?';
buttonText = questdlg(promptMessage, titleBarCaption, 'Yes', 'No', 'Yes');
if contains(buttonText, 'No', 'IgnoreCase', true)
again = false;
end
end
By distinct I mean that each ROI blob needs to be looked at separately. I am going to calculate the sum inside each ROI and tabulate them essentially as region 1, region 2, region 3...
When I added the line you suggested it generated an error: Undefined function 'contains' for input arguments of type 'char'. This could be due to contains being introduced in 2016. strfind is an alternative but it has a different output as far as I can tell.
Image Analyst
Image Analyst on 13 Jul 2017
Use
if strcmpi(buttonText, 'No')
To analyze all the blobs, if you want one of the measurements done by regionprops(), just pass in a labeled version of final image:
labeledImage = bwlabel(finalImage);
props = regionprops(labeledImage, 'all');
This will give you a structure with all kinds of measurements about each individual blob. You can get them out into a single array if you want, for example to get all the areas:
allAreas = [props.Area];
If you want the sum of all the gray levels instead of the sum of pixels (i.e. pixel count), use 'MeanIntensity' and pass in the gray scale image also:
props = regionprops(labeledImage, grayImage, 'Area', 'MeanIntensity');

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GRAN BADSHAH
GRAN BADSHAH on 16 Feb 2013
Thank you sir i found yours this algorithm / explanation very much helpful regarding my work to define ROI of a medical image and then get it as a separate image.
  2 Comments
Meshooo
Meshooo on 24 Mar 2014
Hi, I would like to know why the size or the rectangle"BW" and "hpoly" are different in the following similar case
x = [4 10 10 4 4];
y = [4 4 10 10 4];
BW = poly2mask(x,y,20,20); %binary image
B = bwboundaries(BW);
b = B{1};
X = b(:, 1);
Y = b(:, 2);
hpoly = roipoly(BW,Y,X);
figure, imshow(BW)
figure, imshow(hpoly)
Any idea?
Thank you.
Meshoo
Image Analyst
Image Analyst on 24 Mar 2014
This doesn't seem to be related to Elysi's original question, so please post this as your own question in a separate discussion.

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