Please help me, I need to segment the ventricle of the brain as in this example :
I used region growth but it does not give a good result
MATLAB: How to automatically segment the ventricle of the brain
Image Processing Toolboxsegmentationventricle
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Looking at your original image, I don't know if it was necessary or useful to go through all those steps. I get the impression from the image that if you were to threshold at a sufficiently high grey level, and then imlabel() and regionprops(), that the target area would be the one with the lowest eccentricity.
Try this:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clearvars;workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 16;%=======================================================================================
% Have user browse for a file, from a specified "starting folder."
% For convenience in browsing, set a starting folder from which to browse.
% startingFolder = pwd; % or 'C:\wherever';
% if ~exist(startingFolder, 'dir')
% % If that folder doesn't exist, just start in the current folder.
% startingFolder = pwd;
% end
% % Get the name of the file that the user wants to use.
% defaultFileName = fullfile(startingFolder, 'n*.*');
% [baseFileName, folder] = uigetfile(defaultFileName, 'Select a file');
% if baseFileName == 0
% % User clicked the Cancel button.
% return;
% endfolder = pwd;baseFileName = 'IMG_Segment_Failed.JPG';% baseFileName = 'IMG_Segment_Success.JPEG';
fullFileName = fullfile(folder, baseFileName);rgbImage = imread(fullFileName);% Get the dimensions of the image.
[rows1, columns1, numberOfColorChannels1] = size(rgbImage)% Display the original image.
subplot(2, 2, 1);imshow(rgbImage, []);axis('on', 'image');caption = sprintf('Original Color Image\n"%s"', baseFileName);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by Image Analyst', 'NumberTitle', 'Off')[mask, maskedRGBImage] = createMask(rgbImage);% Display the image.
subplot(2, 2, 2);imshow(mask, []);axis('on', 'image');title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.% Do area filtering.
mask = bwareafilt(mask, [30000, 60000]);% Display the image.subplot(2, 2, 3);imshow(mask, []);axis('on', 'image');title('Mask Image after area filtering', 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.% Measure things in the mask
labeledImage = bwlabel(mask);props = regionprops(labeledImage, 'Area', 'Perimeter');allAreas = [props.Area];% sortedAreas = sort(allAreas)
allPerims = [props.Perimeter];circularities = allPerims .^ 2 ./ (4 * pi * allAreas)subplot(2, 2, 4);% histogram(circularities);
% grid on;
% Extract the roundest blob - the one with circularity closest to 1
[~, index] = min(abs(circularities - 1))mask = ismember(labeledImage, index);imshow(mask, []);axis('on', 'image');title('Mask Image after circularity filtering', 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.function [BW,maskedRGBImage] = createMask(RGB)%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 19-Dec-2019
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.254;channel1Max = 0.991;% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;channel2Max = 1.000;% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;channel3Max = 0.523;% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ... (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ... (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);BW = sliderBW;% Initialize output masked image based on input image.
maskedRGBImage = RGB;% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;end
It might need some tweaking to get it to work with all images.
Or you could try deep learning. I tried imfindcircles() and was not very successful with that function.
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