function [label_meanDist_stdDist, meanDist_stdDist] = evaluate_distances( TEST, TRUE, Labels, verbose )          
%---------------------------------------------------------------------
% This program was used to generate the label boundary distance errors
% for the paper (http://www.mindboggle.info/papers/):
%
% "Evaluation of 14 nonlinear deformation algorithms 
%  applied to human brain MRI registration" 
%  NeuroImage (2009), doi:10.1016/j.neuroimage.2008.12.037
%  by Arno Klein, Jesper Andersson, Babak A. Ardekani, John Ashburner, 
%     Brian Avants, Ming-Chang Chiang, Gary E. Christensen, D. Louis Collins,
%     James Gee, Pierre Hellier, Joo Hyun Song, Mark Jenkinson, Claude Lepage,
%     Daniel Rueckert, Paul Thompson, Tom Vercauteren, Roger P. Woods, 
%     J. John Mann, and Ramin V. Parsey.
%
% Compare two sets of labeled borders for an image volume.
% Determine the average minimum distances from the TRUE to the TEST labels. 
%
% INPUT:  TEST    = 3-D matrix: TEST (usually automated) labels
%         TRUE    = 3-D matrix: TRUE (manually assigned) labels
%         Labels  = list of labels (integers)
%         verbose = 1x1
%
% OUTPUT: [label_meanDist_stdDist, meanDist_stdDist]
%
%--------------------------------------------------------------
% (c) 2008, @rno klein
%--------------------------------------------------------------

  format compact 

  ITEST = find( ismember(TEST,Labels)>0 );
  LTRUE = ismember(TRUE,Labels)>0;
  B = bwdist( (LTRUE==1), 'cityblock' );       
         
  meanDist_stdDist = [mean(B(ITEST)) std(B(ITEST))];
  
  if verbose > 1  
     meanDist_stdDist
  end
  
%--------------------------
% Tally distances per label
%-------------------------- 
  label_meanDist_stdDist = [Labels zeros(size(Labels,1),2)];
  
  for iLabel = 1 : size(Labels,1)
       
      Label = Labels(iLabel);
      
      I=find(TEST==Label);
      
      if size(I,1)>0
          
         B = bwdist( (TRUE==Label), 'cityblock' );       

         label_meanDist_stdDist(iLabel,2:3) = [mean(B(I)) std(B(I))];
         
      else
          
         label_meanDist_stdDist(iLabel,2:3) = [NaN NaN];

      end
  end
  
  if verbose > 1  
     label_meanDist_stdDist
  end