2023_Blaschke_Stroke_tDCS_rsfMRI/scripts/addendum/register_TBI.m

parent_path = "F:\Projects\CBIrep_Imaging\subjects";
cd (parent_path)
addpath("..\scripts\toolbox\DVARS-master\")
addpath("..\scripts\toolbox\DVARS-master\Nifti_Util\")
addpath("..\scripts")
addpath("..\scripts\toolbox\spm12")
addpath("..\scripts\toolbox\fMRI-Quality-Checker-master")
addpath("..\scripts\toolbox\spm12\matlabbatch")
addpath("..\scripts\toolbox\nifti_utils-master\")
%%
px = dir('sub*');

master = zeros(300,5);
noPhysio = zeros(300);

tick = 1;
tack = 1;
%%
% level of subjects
for i = 50:length(px)
    cd (parent_path)
    subject = px(i).name;
    cd (subject)
    cd ("MRI")
    tx = dir("tp*");

    
    % level of timepoints
    for k = 1:length(tx)
        cd (fullfile(parent_path,subject,"MRI"))
        time = tx(k).name;
        cd (time)

        % check for missing physiodata in dataset
% %         if exist("physio","dir")==7
% %             cd ("physio\")
% %             kx = dir;
% %             if length(kx)<3
% %                 noPhysio(tack,1) = strcat(subject,"_",time);
% %                 tack = tack+1;
% %             end
% %         else
% %             noPhysio(tack,1) = strcat(subject,"_",time);
% %             tack = tack+1;
% %         end
        
        % a) get structural 
        if exist(fullfile(parent_path,subject,"MRI",time,"T2w/"))==7 && exist (fullfile(parent_path,subject,"MRI",time,"fMRI/"))==7
            cd (fullfile(parent_path,subject,"MRI",time,"T2w/"))
            struct_orig = dir("*.1.nii.gz");
            struct_name = struct_orig(length(struct_orig)).name;  
            struct_fullfile = fullfile(struct_orig(length(struct_orig)).folder,struct_orig(length(struct_orig)).name); 
            
            struct_reg = dir("*BiasBet_AnnorsfMRI.nii.gz");
            if ~isempty(struct_reg)
            structReg_fullfile = fullfile(struct_reg.folder,struct_reg.name);
            end
            struct_BET = dir("*BiasBet.nii.gz");
            structBET_fullfile = fullfile(struct_BET.folder,struct_BET.name);


        % b) get fMRI
            cd (fullfile(parent_path,subject,"MRI",time,"fMRI/"))
            fmri_orig = dir("*.1.nii.gz");
            fmri_name = fmri_orig(length(fmri_orig)).name;
            fMRI_fullfile = fullfile(fmri_orig(length(fmri_orig)).folder,fmri_orig(length(fmri_orig)).name); 
            fmri_smooth = dir("*SmoothBet.nii.gz");
            fmriSmooth_fullfile = fullfile(fmri_smooth.folder,fmri_smooth.name);

            if ~exist("analyses","dir")
                mkdir("analyses")
            end
            cd ("analyses")

        % c) get Regression File
            cd (fullfile(parent_path,subject,"MRI",time,"fMRI/"))
            ABAreg_orig = dir("*SmoothBet_AnnoSplit_rsfMRI.nii.gz");
            if ~isempty(ABAreg_orig)
            ABAreg_fullfile = fullfile(ABAreg_orig.folder,ABAreg_orig.name);
            end
            cd regr\
            SFRGR_orig = dir("*_SFRGR.nii.gz");
            if ~isempty(SFRGR_orig)
            SFRGR_fullfile = fullfile(SFRGR_orig.folder,SFRGR_orig.name);
            else
                SFRGR_fullfile = [];
            end
        % plot raw images to check registration
            
             
            fMRI_imag = niftiread(fmriSmooth_fullfile);
            fMRI_imag = imrotate(fMRI_imag,-90);
            
            if ~isempty(ABAreg_orig)
            fMRI_Reg = niftiread(ABAreg_fullfile);
            fMRI_Reg = imrotate(fMRI_Reg,-90);
            else
                fMRI_Reg = zeros(96,96,16);
            end

            T2raw = niftiread(structBET_fullfile);
            T2raw = imrotate(T2raw,-90);
            if ~isempty(struct_reg)
            T2Reg = niftiread(structReg_fullfile);
            T2Reg = imrotate(T2Reg,-90);
            else
                T2Reg = zeros(256,256,28);
            end
            
            Loc = [8 13];
%%
                        figure('units','normalized','outerposition',[0 0 1 1])
                        for ix = 1:2
                            % Raw T2w
                            subplot(2,4,1+(4*(ix-1)))
                                imagesc(T2raw(:,:,floor(Loc(ix)/16*28)))
                                colormap("hot")
                            % T2 ARA Reg
                            subplot(2,4,2+(4*(ix-1)))
                                imagesc(T2Reg(:,:,floor(Loc(ix)/16*28)))
%                                 colormap("hot") 
                            % Raw fMRI
                            subplot(2,4,3+(4*(ix-1)))
                                imagesc(fMRI_imag(:,:,Loc(ix)))
%                                 colormap("gray")
                            % fMRI ARA Reg
                            subplot(2,4,4+(4*(ix-1)))
                                imagesc(fMRI_Reg(:,:,Loc(ix)))
%                                 colormap("hot")
                        end
                        title(strcat(subject,'-',time))
             pause
             close
  %%
             RegQuali{tick,1}=subject;
             RegQuali{tick,2}=time;
             
             % get input of image quality
             checkT2    = input("is T2 ok? Y/N [Y]");
             if isempty(checkT2)
                 checkT2 = "Y";
             else 
                 checkT2 = "N";
             end
             RegQuali{tick,3} = checkT2;
             
             checkfMRI  = input("is fMRI ok? Y/N [Y]");
             if isempty(checkfMRI)
                 checkfMRI = "Y";
             else 
                 checkfMRI = "N";
             end
             disp('')
             RegQuali{tick,4} = checkfMRI;

             tick = tick + 1;

   %%
                        
                        
           

% %         % get DVARS
% %         V1 = load_untouch_nii(fMRI_fullfile);
% %         V2 = V1.img;
% %         X0 = size(V2,1); Y0 = size(V2,2); Z0 = size(V2,3); T0 = size(V2,4);
% %         I0 = prod([X0,Y0,Z0]);
% %         Y  = reshape(V2,[I0,T0]); clear V2 V1;
% %         [DVARS,DVARS_Stat]=DVARSCalc(Y,'scale',1/100,'TransPower',1/3,'RDVARS','verbose',1);
% %         [V,DSE_Stat]=DSEvars(Y,'scale',1/100);
% %     %         fMRIDiag_plot(V,DVARS_Stat)
% %     %         saveas(gcf,strcat(fmri_name(1:end-7),'_',"DVARS_plot.png"))
% %     %         pause(2)
% %     %         close all
% % 
% %         bad_points = find(DVARS_Stat.pvals<0.001);
% %         bad_points (bad_points<5)=[];
% %         bad_points = bad_points-4;
% %         perc_bad = length(bad_points)/1.05;
% %             disp("amount of bad points: ")
% %             disp(num2str(perc_bad))
% %             disp("%")
% % 
% %         bad_points_list{tick,1} = fmri_name;
% %         bad_points_list{tick,2} = bad_points;
% %         bad_points_list{tick,4} = mean(DSE_Stat.DeltapDvar(6:end));
% %         bad_points_list{tick,5} = mean(DSE_Stat.DeltapSvar(6:end));
% %         bad_points_list{tick,6} = bad_points;
% %         
% % 
% %         % getFD
% %         cd (fullfile(parent_path,subject,"MRI",time,"fMRI/"))
% %         if exist("txtRegrPython","dir")
% %         cd txtRegrPython\
% %         txtRegr_files = dir("*mcf*");
% %         if size(txtRegr_files,1)>1
% %         txtRegr = txtRegr_files(floor(length(txtRegr_files)/2)).name;
% %         txtRegr_table = readtable(txtRegr);
% %             if ~isempty(txtRegr_table)
% %                 Regression_parameters = txtRegr_table(:,5:10);
% %                 MP = cell2mat(table2cell(Regression_parameters));
% %                 FD_measures = calculateFD(MP, .5, 0.5);
% %                 FD = FD_measures.FD_outliers_ind;
% %             else
% %                 FD = [];
% %             end
% %         else 
% %             FD = [];
% %         end
% %         else
% %             FD = [];
% %         end
% % 
% %         bad_points_list{tick,3} = FD;




%         spm_dir = "F:\Projects\CBIrep_Imaging\scripts\toolbox\spm12";
%         out_dir = pwd;
%         functional4D_fn = char(gunzip(fMRI_fullfile));
%         functional4D_fn = fullfile(fmri_orig.folder,functional4D_fn);
%         structural_fn = char(gunzip(struct_fullfile));
%         structural_fn = fullfile(struct_orig.folder,structural_fn);
%         fwhm = 0.3;
%         calculateQCmeasures(functional4D_fn, structural_fn, fwhm, spm_dir, out_dir, subject)
       
        end
    end
end





       
% % 
% %         % level of individual datasets
% %         for m = 1:length(tix)
% %             cd (fullfile(parent_path,trial,time))
% %             dataset = tix(m).name;
% % 
% %             % find corresponding Physio dataset
% %             physioID = find(~cellfun('isempty',regexp({phx.name},dataset,'once')));
% %             if ~isempty(physioID)
% %                 physiofolder = fullfile(Physio_path,phx(physioID).name);
% %                 master {tick,5} = "y";
% %             else
% %                 noPhysio{tack} = dataset;
% %                 tack = tack +1; 
% %                 master {tick,5} = "n";
% %             end
% %            
% %             sjx = strfind(dataset,'_');
% %             subject = dataset(sjx(2)+3:sjx(3)-1);
% %             
% %             master {tick,1} = subject; 
% %             master {tick,2} = num2str(length(tx)); 
% %             master {tick,3} = dataset;
% %             master {tick,4} = subject;
% % 
% %             disp(strcat("running dataset:",dataset));
% %             cd(dataset)
% % 
% %             % copy data to BIDS
% %             folder_from = pwd;
% %             folder_to = fullfile(BIDS_path,strcat("sub-",subject),"MRI",time);
% %               
% %                 if ~exist("folder_to","dir")
% %                     mkdir(folder_to)
% %                 end
% %                 % copy MRI data
% % %                 copyfile(folder_from,folder_to)
% %                 tick = tick +1;
% % 
% %                 % copy physio data
% %             if exist("physiofolder","var")
% %                 physio_to = fullfile(folder_to,"physio",phx(physioID).name);
% %                 if ~exist(physio_to,"dir")
% %                     mkdir(physio_to)
% %                 end
% % %                 copyfile(physiofolder,physio_to);
% %             end
% %         end
% %                
% % 
% %     end
% % 
% % end