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a b/combinedDeepLearningActiveContour/sortData.m
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% read mat files and store them as a 3D matrix for further processing
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clc 
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close all
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clear all
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%%
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imset='training';
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%imset='validation';
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%imset='online';
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folder=['matFiles/',imset,'/ED/'];
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D=dir([folder,'\*.mat']);
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numpatients = length(D(not([D.isdir])));
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t_I=[];
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t_yROI=[];
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t_Iroi=[];
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t_yLV=[];
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t_yMC=[];
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t_contoursLV=[];
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t_contoursMC=[];
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t_centers=[];
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t_LV_cont_names=[];
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t_MC_cont_names=[];
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for k=1:numpatients
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    imgname=['matFiles/',imset,'/ED/ED_P',num2str(k)];
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%    yname=['matFiles/',imset,'/yROI_ED',num2str(k)];
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    load (imgname);
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%    load (yname);
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    t_I=cat(3,t_I,I);
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    t_yROI=cat(3,t_yROI,yROI);
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    t_Iroi=cat(3,t_Iroi,Iroi);
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    t_yLV=cat(3,t_yLV,yLV);
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    t_yMC=cat(3,t_yMC,yMC);
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    t_contoursLV=[t_contoursLV,contours_LV(1:size(I,3))];
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    t_contoursMC=[t_contoursMC,contours_MC(1:size(I,3))];
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    t_centers=[t_centers,contour_center(1:size(I,3))];
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    slice_per_patient(k)=size(I,3);
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    t_LV_cont_names=[t_LV_cont_names;LV_contours_names];
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    t_MC_cont_names=[t_MC_cont_names;MC_contours_names];
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end
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filename=['matFiles/',imset,'_dataED'];
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save (filename,'t_I','t_yROI','t_Iroi','t_yLV','t_yMC','t_contoursLV','t_contoursMC','t_centers','numpatients',...
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'slice_per_patient','t_LV_cont_names','t_MC_cont_names');
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display('file has been saved')