MATLAB: How to perform region growing with two seed points

Image Processing Toolboximage segmentationmriregion growing

Hi everyone!
I have some images of the carotid artery, and I need to segment the image to obtain the outer wall and the plaque region. I used a function posted here (region growing from one seed point), and I tried to modify it. I want the function to have two seeded points, but my function doesn't work. Can you please give me some suggestion?
This is for my school project. 
function J=RG2incerc(I,x,y,x2,y2,reg_maxdist1,reg_maxdist2)
% 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_maxdist1','var')==0), reg_maxdist1=0.2; end
if(exist('y','var')==0), figure, imshow(I,[]); [y1,x1]=getpts; y=round(y(1)); x=round(x(1)); end
 
J = zeros(size(I)); % Output 
J2=zeros(size(I));
Isizes = size(I); % Dimensions of input image
 
reg_mean = I(x,y); % The mean of the segmented region
reg_mean2=I(x2,y2);
reg_size = 1; % Number of pixels in region
reg_size2=1;
 
% Free memory to store neighbours of the (segmented) region
neg_free = 10000; neg_pos=0; neg_free2=10000; neg_pos2=0;
neg_list = zeros(neg_free,3); neg_list2 = zeros(neg_free2,3); 
pixdist=0; % Distance of the region newest pixel to the regio mean
pixdist2=0;
 
% Neighbor locations (footprint)
neigb=[-1 0; 1 0; 0 -1;0 1]; 
neigb2=[-1 0; 1 0; 0 -1;0 1];
% Start regiogrowing until distance between regio and posible new pixels become
% higher than a certain treshold
while(pixdist<reg_maxdist1&&reg_size<numel(I))
    % 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;
end 
J=J>1;
while(pixdist2<reg_maxdist2&&reg_size2<numel(I))
 
    % Add new neighbors pixels
    for j=1:4,
        % Calculate the neighbour coordinate
        xn = x2 +neigb(j,1); yn = y2 +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_pos2 = neg_pos2+1;
                neg_list2(neg_pos2,:) = [xn yn I(xn,yn)]; J2(xn,yn)=1;
        end
    end
% Add a new block of free memory
    if(neg_pos2+10>neg_free2), neg_free2=neg_free2+10000; neg_list2((neg_pos2+1):neg_free2,:)=0; end
 
dist2 = abs(neg_list2(1:neg_pos2,3)-reg_mean2);
    [pixdist2, index] = min(dist2);
    J2(x,y)=2; reg_size2=reg_size+1;
% Calculate the new mean of the region
    reg_mean2= (reg_mean2*reg_size2 + neg_list2(index,3))/(reg_size2+1);
x2 = neg_list2(index,1); y2 = neg_list2(index,2);
% Remove the pixel from the neighbour (check) list
    neg_list2(index,:)=neg_list2(neg_pos2,:); neg_pos2=neg_pos2-1;
end
J2=J2>1;

Best Answer

Can you upload an image, and give examples of the values: I,x,y,x2,y2,reg_maxdist1,reg_maxdist2, then we can run the code and check whats wrong.
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