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Copy pathIDEALevalTri.m
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IDEALevalTri.m
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function [FitQuality,ROIstat] = IDEALevalTri(Mask,FitResults,gof,output,DataNii,P,ROIs,ROINii,Data,MaskNii,model)
%% Extract the parameters maps
f_slow = nan(size(Mask));
f_interm = nan(size(Mask));
f_fast = nan(size(Mask));
D_slow = nan(size(Mask));
D_interm = nan(size(Mask));
D_fast = nan(size(Mask));
S_0 = nan(size(Mask));
SSE = nan(size(Mask));
Rsq = nan(size(Mask));
Dfe = nan(size(Mask));
AdjRsq = nan(size(Mask));
RMSE = nan(size(Mask));
Residuals = nan(size(Mask, 1), size(Mask, 2), 16);
FitQuality = struct();
for kx = 1:size(Mask, 1)
for ky = 1:size(Mask, 2)
if ~isempty(FitResults{kx,ky})
f_slow(kx, ky) = 1 - FitResults{kx,ky}.a - FitResults{kx,ky}.b;
f_interm(kx, ky) = FitResults{kx,ky}.a;
f_fast(kx, ky) = FitResults{kx,ky}.b;
D_slow(kx, ky) = FitResults{kx,ky}.c;
D_interm(kx, ky) = FitResults{kx,ky}.d;
D_fast(kx, ky) = FitResults{kx,ky}.e;
S_0(kx, ky) = FitResults{kx,ky}.f;
FitQuality.SSE(kx, ky) = gof{kx,ky}.sse;
FitQuality.Rsq(kx, ky) = gof{kx,ky}.rsquare;
FitQuality.Dfe(kx, ky) = gof{kx,ky}.dfe;
FitQuality.AdjRsq(kx, ky) = gof{kx,ky}.adjrsquare;
FitQuality.RMSE(kx, ky) = gof{kx,ky}.rmse;
FitQuality.Residuals(kx, ky, :) = output{kx,ky}.residuals;
end
end
end
%% Plot the parameter maps
[~,file_name,~] = fileparts(DataNii);
if P.plot
figure('Visible','on')
subplot(3,3,1)
imagesc(f_slow);
caxis(gca,[0 1])
title('f_{slow}')
colormap gray;
axis off;
subplot(3,3,2)
imagesc(f_interm);
caxis(gca,[0 1])
title('f_{interm}')
colormap gray;
axis off;
subplot(3,3,3)
imagesc(f_fast);
caxis(gca,[0 1])
title('f_{fast}')
colormap gray;
axis off;
subplot(3,3,4)
imagesc(D_slow);
title('D_{slow}')
colormap gray;
axis off;
subplot(3,3,5)
imagesc(D_interm);
title('D_{interm}')
colormap gray;
axis off;
subplot(3,3,6)
imagesc(D_fast);
title('D_{fast}')
colormap gray;
axis off;
subplot(3,3,7)
imagesc(S_0);
title('S_{0,fit}');
colormap gray;
axis off;
subplot(3,3,8)
imagesc(squeeze(Data(:, :, 1)));
title('S_{0}');
colormap gray;
axis off;
if ~exist(P.outputFolder)
mkdir(P.outputFolder);
end
fignm_param = sprintf('%s%sIDEALfit_%s_steps_%s_param.fig',...
P.outputFolder, filesep, file_name, num2str(size(P.Dims_steps,1)));
savefig(gcf, fignm_param);
close(gcf);
end
ROIstat = eval_rois(ROIs,ROINii,MaskNii,f_slow,f_interm,f_fast,D_slow,D_interm,D_fast,S_0);
filenm = sprintf('%s%sIDEALfit%s_steps_%s.mat',...
P.outputFolder, filesep, file_name, num2str(size(P.Dims_steps, 1)));
save(filenm);
end
function ROIstat = eval_rois(ROIs,ROINii,MaskNii,f_slow,f_interm,f_fast,D_slow,D_interm,D_fast,S_0)
%% Perform ROI-based analysis
ROIstat.ROIname = cell(1,length(ROIs));
IVIMPars = {'f_slow','f_interm','f_fast','D_slow','D_interm','D_fast','S_0'};
for par = 1 : length(IVIMPars)
ROIstat.(IVIMPars{par}).mean = zeros(1,length(ROIs));
ROIstat.(IVIMPars{par}).median = zeros(1,length(ROIs));
ROIstat.(IVIMPars{par}).std = zeros(1,length(ROIs));
ROIstat.(IVIMPars{par}).CV = zeros(1,length(ROIs));
ROIstat.(IVIMPars{par}).iqr = zeros(1,length(ROIs));
ROIstat.(IVIMPars{par}).q1 = zeros(1,length(ROIs));
ROIstat.(IVIMPars{par}).q3 = zeros(1,length(ROIs));
end
version_num = split(version(),' ');
version_num = split(version_num{1},'.');
version_num = join(version_num(1:2),'.');
version_num = str2num(version_num{1});
if version_num > 9.4
for rois = 1 : length(ROIs)
if rois == 1
[~,name,~] = fileparts(MaskNii);
else
[~,name,~] = fileparts(ROINii{rois-1});
end
ROIstat.ROIname{rois} = name;
for par = 1 : length(IVIMPars)
eval(['ROIstat.' IVIMPars{par} '.mean(rois) = nanmean(' IVIMPars{par} '(ROIs{rois}==1),''all'');']);
eval(['ROIstat.' IVIMPars{par} '.median(rois) = nanmedian(' IVIMPars{par} '(ROIs{rois}==1),''all'');']);
eval(['ROIstat.' IVIMPars{par} '.std(rois) = nanstd(' IVIMPars{par} '(ROIs{rois}==1),0,''all'');']);
eval(['ROIstat.' IVIMPars{par} '.CV(rois) = ROIstat.' IVIMPars{par} '.std(rois) /ROIstat.' IVIMPars{par} '.mean(rois);']);
eval(['ROIstat.' IVIMPars{par} '.iqr(rois) = iqr(reshape(' IVIMPars{par} '(ROIs{rois}==1),[],1));']);
eval(['ROIstat.' IVIMPars{par} '.q1(rois) = prctile(reshape(' IVIMPars{par} '(ROIs{rois}==1),[],1),25);']);
eval(['ROIstat.' IVIMPars{par} '.q3(rois) = prctile(reshape(' IVIMPars{par} '(ROIs{rois}==1),[],1),1);']);
end
end
elseif version_num <= 9.4
for rois = 1 : length(ROIs)
if rois == 1
[~,name,~] = fileparts(MaskNii);
else
[~,name,~] = fileparts(ROINii{rois-1});
end
ROIstat.ROIname{rois} = name;
for par = 1 : length(IVIMPars)
eval(['ROIstat.' IVIMPars{par} '.mean(rois) = nanmean(' IVIMPars{par} '(ROIs{rois}==1));']);
eval(['ROIstat.' IVIMPars{par} '.median(rois) = nanmedian(' IVIMPars{par} '(ROIs{rois}==1));']);
eval(['ROIstat.' IVIMPars{par} '.std(rois) = nanstd(' IVIMPars{par} '(ROIs{rois}==1),0);']);
eval(['ROIstat.' IVIMPars{par} '.CV(rois) = ROIstat.' IVIMPars{par} '.std(rois) /ROIstat.' IVIMPars{par} '.mean(rois);']);
eval(['ROIstat.' IVIMPars{par} '.iqr(rois) = iqr(reshape(' IVIMPars{par} '(ROIs{rois}==1),[],1));']);
eval(['ROIstat.' IVIMPars{par} '.q1(rois) = prctile(reshape(' IVIMPars{par} '(ROIs{rois}==1),[],1),25);']);
eval(['ROIstat.' IVIMPars{par} '.q3(rois) = prctile(reshape(' IVIMPars{par} '(ROIs{rois}==1),[],1),1);']);
end
end
end
end