使用Matlab進行腫瘤分割的模糊C手段

Question

我有一個分段肝臟。我需要在其中分割腫瘤。我使用FCM方法。這是一個3級FCM閾值。當我將它應用於圖像時，我需要將腫瘤區域（比其餘部分更暗的區域）單獨分割。但是我們正好相反。腫瘤周圍的所有區域都被分割。請幫助我。該方案有兩個文件，testfcmthresh.m和功能fcmthresh.m

輸入「分割的肝臟（使用區域生長）」和FCM輸出圖像：

from here

我試圖補充圖像通過使用imcomplement()獲得但我得到的整個背景也是白色的，因爲背景本來是黑暗的。請幫助我。

function [bw,level]=fcmthresh(IM,sw) 
%FCMTHRESH Thresholding by 3-class fuzzy c-means clustering 
% [bw,level]=fcmthresh(IM,sw) outputs the binary image bw and threshold level of 
% image IM using a 3-class fuzzy c-means clustering. It often works better 
% than Otsu's methold which outputs larger or smaller threshold on 
% fluorescence images. 
% sw is 0 or 1, a switch of cut-off position. 
% sw=0, cut between the small and middle class 
% sw=1, cut between the middle and large class 
% 
% Contributed by Guanglei Xiong (xgl99@mails.tsinghua.edu.cn) 
% at Tsinghua University, Beijing, China. 

% check the parameters 
if (nargin<1) 
    error('You must provide an image.'); 
elseif (nargin==1) 
    sw=0; 
elseif (sw~=0 && sw~=1) 
    error('sw must be 0 or 1.'); 
end 

data=reshape(IM,[],1); 
[center,member]=fcm(data,3); 
[center,cidx]=sort(center); 
member=member'; 
member=member(:,cidx); 
[maxmember,label]=max(member,[],2); 
if sw==0 
    level=(max(data(label==1))+min(data(label==2)))/2; 
else 
    level=(max(data(label==2))+min(data(label==3)))/2; 
end 
bw=im2bw(IM,level); 

---

%testfcmthresh.m 

clear;clc; 
im=imread('mliver3.jpg'); 
fim=mat2gray(im); 
level=graythresh(fim); 
bwfim=im2bw(fim,0.1); 
[bwfim0,level0]=fcmthresh(fim,0); 
[bwfim1,level1]=fcmthresh(fim,1); 
subplot(2,2,1); 
imshow(fim);title('Original'); 
subplot(2,2,2); 
imshow(bwfim);title(sprintf('Otsu,level=%f',level)); 
subplot(2,2,3); 
imshow(bwfim0);title(sprintf('FCM0,level=%f',level0)); 
subplot(2,2,4); 
imshow(bwfim1);title(sprintf('FCM1,level=%f',level1)); 
% imwrite(bwfim1,'fliver6.jpg'); 

Answer 1

我的問題的答案已經在我剛纔的問題'Extracting image region within boundary'已經告訴Ghaul。如果有任何人需要參考，請在此通過Ghaul的評論。謝謝。