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Active contour platform

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Active contour platform

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26 May 2010 (Updated )

Compare the performance of different level sets and active contours methods.

creaseg_plotresults(src,evt)
% Copyright or © or Copr. CREATIS laboratory, Lyon, France.
% 
% Contributor: Olivier Bernard, Associate Professor at the french 
% engineering university INSA (Institut National des Sciences Appliquees) 
% and a member of the CREATIS-LRMN laboratory (CNRS 5220, INSERM U630, 
% INSA, Claude Bernard Lyon 1 University) in France (Lyon).
% 
% Date of creation: 8th of October 2009
% 
% E-mail of the author: olivier.bernard@creatis.insa-lyon.fr
% 
% This software is a computer program whose purpose is to evaluate the 
% performance of different level-set based segmentation algorithms in the 
% context of image processing (and more particularly on biomedical 
% images).
% 
% The software has been designed for two main purposes. 
% - firstly, CREASEG allows you to use six different level-set methods. 
% These methods have been chosen in order to work with a wide range of 
% level-sets. You can select for instance classical methods such as 
% Caselles or Chan & Vese level-set, or more recent approaches such as the 
% one developped by Lankton or Bernard.
% - finally, the software allows you to compare the performance of the six 
% level-set methods on different images. The performance can be evaluated 
% either visually, or from measurements (either using the Dice coefficient 
% or the PSNR value) between a reference and the results of the 
% segmentation.
%  
% The level-set segmentation platform is citationware. If you are 
% publishing any work, where this program has been used, or which used one 
% of the proposed level-set algorithms, please remember that it was 
% obtained free of charge. You must reference the papers shown below and 
% the name of the CREASEG software must be mentioned in the publication.
% 
% CREASEG software
% "T. Dietenbeck, M. Alessandrini, D. Friboulet, O. Bernard. CREASEG: a
% free software for the evaluation of image segmentation algorithms based 
% on level-set. In IEEE International Conference On Image Processing. 
% Hong Kong, China, 2010."
%
% Bernard method
% "O. Bernard, D. Friboulet, P. Thevenaz, M. Unser. Variational B-Spline 
% Level-Set: A Linear Filtering Approach for Fast Deformable Model 
% Evolution. In IEEE Transactions on Image Processing. volume 18, no. 06, 
% pp. 1179-1191, 2009."
% 
% Caselles method
% "V. Caselles, R. Kimmel, and G. Sapiro. Geodesic active contours. 
% International Journal of Computer Vision, volume 22, pp. 61-79, 1997."
% 
% Chan & Vese method
% "T. Chan and L. Vese. Active contours without edges. IEEE Transactions on
% Image Processing. volume10, pp. 266-277, February 2001."
% 
% Lankton method
% "S. Lankton, A. Tannenbaum. Localizing Region-Based Active Contours. In 
% IEEE Transactions on Image Processing. volume 17, no. 11, pp. 2029-2039, 
% 2008."
% 
% Li method
% "C. Li, C.Y. Kao, J.C. Gore, Z. Ding. Minimization of Region-Scalable 
% Fitting Energy for Image Segmentation. In IEEE Transactions on Image 
% Processing. volume 17, no. 10, pp. 1940-1949, 2008."
% 
% Shi method
% "Yonggang Shi, William Clem Karl. A Real-Time Algorithm for the 
% Approximation of Level-Set-Based Curve Evolution. In IEEE Transactions 
% on Image Processing. volume 17, no. 05, pp. 645-656, 2008."
% 
% This software is governed by the BSD license and
% abiding by the rules of distribution of free software.
% 
% As a counterpart to the access to the source code and rights to copy,
% modify and redistribute granted by the license, users are provided only
% with a limited warranty and the software's author, the holder of the
% economic rights, and the successive licensors have only limited
% liability. 
% 
% In this respect, the user's attention is drawn to the risks associated
% with loading, using, modifying and/or developing or reproducing the
% software by the user in light of its specific status of free software,
% that may mean that it is complicated to manipulate, and that also
% therefore means that it is reserved for developers and experienced
% professionals having in-depth computer knowledge. Users are therefore
% encouraged to load and test the software's suitability as regards their
% requirements in conditions enabling the security of their systems and/or 
% data to be ensured and, more generally, to use and operate it in the 
% same conditions as regards security.
% 
%------------------------------------------------------------------------


function creaseg_plotresults(src,evt)

    %-- parameters
    fig = findobj(0,'tag','creaseg');
    ud = get(fig,'userdata');
    fd = get(ud.imageId,'userdata');
    
    if ( isempty(fd.data) )
        return;
    end  
    
   	delete(findobj(get(ud.imageId,'parent'),'type','line'));
    
    color = {'w','y','b','c','r','g','m','k'};
    
    if get(ud.handleAlgoResults(5),'Value')
        show_contour(fd.reference,ud,color(1));
    end
    for i=1:1:7
        if ( get(ud.handleAlgoResults(5+i),'Value') )
            show_contour(fd.seg(:,:,i),ud,color(i+1));
        end
    end
    
   

function show_contour(mask,ud,cl)

	axes(get(ud.imageId,'parent'));
	hold on; [c,h] = contour(mask,[0 0],cl{1},'Linewidth',3); hold off;
	delete(h);
    test = isequal(size(c,2),0);
	while ( (test==false) && (size(c,1) ~= 0) && (size(c,2) ~= 0) )
        s = c(2,1);
        if ( s == (size(c,2)-1) )
            t = c;
            hold on; plot(t(1,2:end)',t(2,2:end)',cl{1},'linewidth',3);
            test = true;
        else
            t = c(:,2:s+1);
            hold on; plot(t(1,1:end)',t(2,1:end)',cl{1},'linewidth',3);
            c = c(:,s+2:end);
        end
	end  
    

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