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segmentation by marking points around the region

Asked by Elysi Cochin on 17 Dec 2012
Latest activity Commented on by Image Analyst on 24 Mar 2014

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.....

0 Comments

Elysi Cochin

3 Answers

Answer by Image Analyst on 17 Dec 2012
Accepted answer

Use roipoly() or roipolyold() and then poly2mask().

9 Comments

Image Analyst on 18 Dec 2012

I thought you were using ginput(), roipoly(), or roipolyold(). All of those can do it. Did you try them? I'm not sure what you want. Do you need an example of how to use them? (Keep in mind that we're not going to write an automatic medical image segmentation application for you - that's way way too much to ask of us.)

Elysi Cochin on 18 Dec 2012

sir roipolyold()function is working sir.... but one thing when we select a portion that part is being cut from the image... i wanted to display that selected part in a figure... is it possible sir....

    I=imread('abdo-ct-norm.jpg');
    BW = ROIPOLYOLD(I);
    imshow(BW);

using the above code the portion i selected will be display in white color and the remaining portion of the figure is black.... i wanted the region i selected to be displayed as it appears in input image and the remaining portion deleted.... that is like cutting a portion from a figure and pasting it in another figure.... please can u help me..

Image Analyst
Answer by 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);

2 Comments

Elysi Cochin on 19 Dec 2012

thank u sir... thank u so much....

Walter Roberson on 16 Nov 2013

Ahmed commented "mask by hand".

Unfortunately the comment does not appear to have enough context to be actionable.

Image Analyst
Answer by 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 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 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.

GRAN  BADSHAH

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