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POExtracting image region within boundary
 

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  1. POExtracting image region within boundary
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    <p>I have to do a project using 2D CT images and segment liver and tumor in it using Matlab(only). Initially i have to segment liver region alone. I use region growing for liver segmentation. It gets seed point as input. </p> <p>The output is an image with a boundary for liver region. Now I need the region that is surrounded by the boundary alone. </p> <p>My program has a main program and a regionGrowing.m function. As I'm a new user am not allowed to post images. If you do need images I will mail you. Kindly help me.</p> <pre><code> % mainreg.m IR=imread('nfliver5.jpg'); figure, imshow(IR), hold all poly = regionGrowing(IR,[],15,1200); % click somewhere inside the liver plot(poly(:,1), poly(:,2), 'LineWidth', 2, 'Color', [1 1 1]) </code></pre> <hr> <pre><code>%regionGrowing.m function [P, J] = regionGrowing(cIM, initPos, thresVal, maxDist, tfMean, tfFillHoles, tfSimplify) % REGIONGROWING Region growing algorithm for 2D/3D grayscale images % % Syntax: % P = regionGrowing(); % P = regionGrowing(cIM); % P = regionGrowing(cIM, initPos) % P = regionGrowing(..., thresVal, maxDist, tfMean, tfFillHoles, tfSimpl) % [P, J] = regionGrowing(...); % % Inputs: % cIM: 2D/3D grayscale matrix {current image} % initPos: Coordinates for initial seed position {ginput position} % thresVal: Absolute threshold level to be included {5% of max-min} % maxDist: Maximum distance to the initial position in [px] {Inf} % tfMean: Updates the initial value to the region mean (slow) {false} % tfFillHoles: Fills enclosed holes in the binary mask {true} % tfSimplify: Reduces the number of vertices {true, if dpsimplify exists} % % Outputs: % P: VxN array (with V number of vertices, N number of dimensions) % P is the enclosing polygon for all associated pixel/voxel % J: Binary mask (with the same size as the input image) indicating % 1 (true) for associated pixel/voxel and 0 (false) for outside % % Examples: % % 2D Example % load example % figure, imshow(cIM, [0 1500]), hold all % poly = regionGrowing(cIM, [], 300); % click somewhere inside the lungs % plot(poly(:,1), poly(:,2), 'LineWidth', 2) % % % 3D Example % load mri % poly = regionGrowing(squeeze(D), [66,55,13], 60, Inf, [], true, false); % plot3(poly(:,1), poly(:,2), poly(:,3), 'x', 'LineWidth', 2) % % Requirements: % TheMathWorks Image Processing Toolbox for bwboundaries() and axes2pix() % Optional: Line Simplification by Wolfgang Schwanghart to reduce the % number of polygon vertices (see the MATLAB FileExchange) % % Remarks: % The queue is not preallocated and the region mean computation is slow. % I haven't implemented a preallocation nor a queue counter yet for the % sake of clarity, however this would be of course more efficient. % % Author: % Daniel Kellner, 2011, braggpeaks{}googlemail.com % History: v1.00: 2011/08/14 % error checking on input arguments if nargin &gt; 7 error('Wrong number of input arguments!') end if ~exist('cIM', 'var') himage = findobj('Type', 'image'); if isempty(himage) || length(himage) &gt; 1 error('Please define one of the current images!') end cIM = get(himage, 'CData'); end if ~exist('initPos', 'var') || isempty(initPos) himage = findobj('Type', 'image'); if isempty(himage) himage = imshow(cIM, []); end % graphical user input for the initial position p = ginput(1); % get the pixel position concerning to the current axes coordinates initPos(1) = round(axes2pix(size(cIM, 2), get(himage, 'XData'), p(2))); initPos(2) = round(axes2pix(size(cIM, 1), get(himage, 'YData'), p(1))); end if ~exist('thresVal', 'var') || isempty(thresVal) thresVal = double((max(cIM(:)) - min(cIM(:)))) * 0.05; end if ~exist('maxDist', 'var') || isempty(maxDist) maxDist = Inf; end if ~exist('tfMean', 'var') || isempty(tfMean) tfMean = false; end if ~exist('tfFillHoles', 'var') tfFillHoles = true; end if isequal(ndims(cIM), 2) initPos(3) = 1; elseif isequal(ndims(cIM),1) || ndims(cIM) &gt; 3 error('There are only 2D images and 3D image sets allowed!') end [nRow, nCol, nSli] = size(cIM); if initPos(1) &lt; 1 || initPos(2) &lt; 1 ||... initPos(1) &gt; nRow || initPos(2) &gt; nCol error('Initial position out of bounds, please try again!') end if thresVal &lt; 0 || maxDist &lt; 0 error('Threshold and maximum distance values must be positive!') end if ~isempty(which('dpsimplify.m')) if ~exist('tfSimplify', 'var') tfSimplify = true; end simplifyTolerance = 1; else tfSimplify = false; end % initial pixel value regVal = double(cIM(initPos(1), initPos(2), initPos(3))); % text output with initial parameters disp(['RegionGrowing Opening: Initial position (' num2str(initPos(1))... '|' num2str(initPos(2)) '|' num2str(initPos(3)) ') with '... num2str(regVal) ' as initial pixel value!']) % preallocate array J = false(nRow, nCol, nSli); % add the initial pixel to the queue queue = [initPos(1), initPos(2), initPos(3)]; %%% START OF REGION GROWING ALGORITHM while size(queue, 1) % the first queue position determines the new values xv = queue(1,1); yv = queue(1,2); zv = queue(1,3); % .. and delete the first queue position queue(1,:) = []; % check the neighbors for the current position for i = -1:1 for j = -1:1 for k = -1:1 if xv+i &gt; 0 &amp;&amp; xv+i &lt;= nRow &amp;&amp;... % within the x-bounds? yv+j &gt; 0 &amp;&amp; yv+j &lt;= nCol &amp;&amp;... % within the y-bounds? zv+k &gt; 0 &amp;&amp; zv+k &lt;= nSli &amp;&amp;... % within the z-bounds? any([i, j, k]) &amp;&amp;... % i/j/k of (0/0/0) is redundant! ~J(xv+i, yv+j, zv+k) &amp;&amp;... % pixelposition already set? sqrt( (xv+i-initPos(1))^2 +... (yv+j-initPos(2))^2 +... (zv+k-initPos(3))^2 ) &lt; maxDist &amp;&amp;... % within distance? cIM(xv+i, yv+j, zv+k) &lt;= (regVal + thresVal) &amp;&amp;...% within range cIM(xv+i, yv+j, zv+k) &gt;= (regVal - thresVal) % of the threshold? % current pixel is true, if all properties are fullfilled J(xv+i, yv+j, zv+k) = true; % add the current pixel to the computation queue (recursive) queue(end+1,:) = [xv+i, yv+j, zv+k]; if tfMean regVal = mean(mean(cIM(J &gt; 0))); % --&gt; slow! end end end end end end %%% END OF REGION GROWING ALGORITHM % loop through each slice, fill holes and extract the polygon vertices P = []; for cSli = 1:nSli if ~any(J(:,:,cSli)) continue end % use bwboundaries() to extract the enclosing polygon if tfFillHoles % fill the holes inside the mask J(:,:,cSli) = imfill(J(:,:,cSli), 'holes'); B = bwboundaries(J(:,:,cSli), 8, 'noholes'); else B = bwboundaries(J(:,:,cSli)); end newVertices = [B{1}(:,2), B{1}(:,1)]; % simplify the polygon via Line Simplification if tfSimplify newVertices = dpsimplify(newVertices, simplifyTolerance); end % number of new vertices to be added nNew = size(newVertices, 1); % append the new vertices to the existing polygon matrix if isequal(nSli, 1) % 2D P(end+1:end+nNew, :) = newVertices; else % 3D P(end+1:end+nNew, :) = [newVertices, repmat(cSli, nNew, 1)]; end end % text output with final number of vertices disp(['RegionGrowing Ending: Found ' num2str(length(find(J)))... ' pixels within the threshold range (' num2str(size(P, 1))... ' polygon vertices)!']) </code></pre>
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    1. COI have cleaned up your questions somewhat and given it what I think is a relevant title. Keep it to the point. If truly necessary, put the images somewhere online and we can add them to your question for you.
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