% This Matlab script illustrate how to use two images as input for FCM segmentation
clc
clear all
%Load GADO image
info = imfinfo('GADOimage.jpg');
I = im2double(imread('GADOimage','jpg'));
I = imadjust(I);
%Load AXIAL FLAIR image
info2 = imfinfo('FLAIRimage.jpg');
I2 = im2double(imread('FLAIRimage','jpg'));
I2 = imadjust(I);
figure;imshow(I,[]);impixelinfo; % Show Image I
data = [I(:) I2(:)]; % data array
[center,U,obj_fcn] = fcm(data,7); % Fuzzy C-means classification with 7 classes
% Finding the pixels for each class
maxU = max(U);
index1 = find(U(1,:) == maxU);
index2 = find(U(2,:) == maxU);
index3 = find(U(3,:) == maxU);
index4 = find(U(4,:) == maxU);
index5 = find(U(5,:) == maxU);
index6 = find(U(6,:) == maxU);
index7 = find(U(7,:) == maxU);
% Assigning pixel to each class by giving them a specific value
fcmImage(1:length(data))=0;
fcmImage(index1)= 1;
fcmImage(index2)= 0.8;
fcmImage(index3)= 0.6;
fcmImage(index4)= 0.4;
fcmImage(index5)= 0.2;
fcmImage(index6)= 0.1;
fcmImage(index7)= 0.0;
% Reshapeing the array to a image
imagNew = reshape(fcmImage,512,512);
figure;imshow(imagNew,[]);impixelinfo;
B15
