matlab - 区域增长算法给出不正确的结果

Question

我正在应用区域增长算法来分割乳房图像中的肿瘤。左侧的图像是原始图像。中心最亮的地方应该是肿瘤。分割应该只显示那个点。但是，应用该算法后，生成的图像是右侧的图像，这是不准确的。任何建议，将不胜感激。

I = rgb2gray(im2double(imread('TM25.jpg')));
J=imadjust(I,[],[],0.5);
J=imgaussfilt(J);
J= regiongrowing(J, 64, 64,0.5);
imshowpair(I,J,'montage')

function J=regiongrowing(I,x,y,reg_maxdist)
% This function performs "region growing" in an image from a specified
% seedpoint (x,y)
%
% J = regiongrowing(I,x,y,t) 
% 
% I : input image 
% J : logical output image of region
% x,y : the position of the seedpoint (if not given uses function getpts)
% t : maximum intensity distance (defaults to 0.2)
%
% The region is iteratively grown by comparing all unallocated neighbouring pixels to the region. 
% The difference between a pixel's intensity value and the region's mean, 
% is used as a measure of similarity. The pixel with the smallest difference 
% measured this way is allocated to the respective region. 
% This process stops when the intensity difference between region mean and
% new pixel become larger than a certain treshold (t)
%
% Example:
%
% I = im2double(imread('medtest.png'));
% x=198; y=359;
% J = regiongrowing(I,x,y,0.2); 
% figure, imshow(I+J);
%
% Author: D. Kroon, University of Twente

if(exist('reg_maxdist','var')==0), reg_maxdist=0.2; end
if(exist('y','var')==0), figure, imshow(I,[]); [y,x]=getpts; y=round(y(1)); x=round(x(1)); end

J = zeros(size(I)); % Output 
Isizes = size(I); % Dimensions of input image

reg_mean = I(x,y); % The mean of the segmented region
reg_size = 1; % Number of pixels in region

% Free memory to store neighbours of the (segmented) region
neg_free = 10000; neg_pos=0;
neg_list = zeros(neg_free,3); 

pixdist=0; % Distance of the region newest pixel to the regio mean

% Neighbor locations (footprint)
neigb=[-1 0; 1 0; 0 -1;0 1];
diff = 01;
% Start regiogrowing until distance between regio and posible new pixels become
% higher than a certain treshold
while(pixdist<reg_maxdist && reg_size<numel(I) && diff ~=0)
    num1 = sum(sum(reg_size));
    % Add new neighbors pixels
    for j=1:4,
        % Calculate the neighbour coordinate
        xn = x +neigb(j,1); yn = y +neigb(j,2);
        
        % Check if neighbour is inside or outside the image
        ins=(xn>=1)&&(yn>=1)&&(xn<=Isizes(1))&&(yn<=Isizes(2));
        
        % Add neighbor if inside and not already part of the segmented area
        if(ins&&(J(xn,yn)==0)) 
                neg_pos = neg_pos+1;
                neg_list(neg_pos,:) = [xn yn I(xn,yn)]; J(xn,yn)=1;
        end
    end

    % Add a new block of free memory
    if(neg_pos+10>neg_free), neg_free=neg_free+10000; neg_list((neg_pos+1):neg_free,:)=0; end
    
    % Add pixel with intensity nearest to the mean of the region, to the region
    dist = abs(neg_list(1:neg_pos,3)-reg_mean);
    [pixdist, index] = min(dist);
    J(x,y)=2; reg_size=reg_size+1;
    
    % Calculate the new mean of the region
    reg_mean= (reg_mean*reg_size + neg_list(index,3))/(reg_size+1);
    
    % Save the x and y coordinates of the pixel (for the neighbour add proccess)
    x = neg_list(index,1); y = neg_list(index,2);
    
    % Remove the pixel from the neighbour (check) list
    neg_list(index,:)=neg_list(neg_pos,:); neg_pos=neg_pos-1;
    num2 = sum(sum(reg_size));
    diff = num2-num1;
end

% Return the segmented area as logical matrix
J=J>1;

标签： matlab

Answer 1

区域增长是一个非常简单的算法。简而言之，它说“如果下一个像素reg_maxdist的像素值小于当前像素，则它是该区域的一部分，否则它不是”。

您的图像非常流畅。这意味着像素值在相邻像素中变化缓慢，因此区域增长算法会将它们纳入其中。您总是可以稍微玩弄允许的最大像素差异（0 是所有像素都需要是相同的值，1 是所有像素都是一部分地区的），并希望有更好的结果，但不能保证你得到一个好结果。

对于您的图像，我 99% 确定区域增长不会削减它，您将需要使用更复杂的算法。