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Gen_niftis_single_tracts.m
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Gen_niftis_single_tracts.m
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function [] = Gen_niftis_single_tracts(info, tract_name_1, tract_name_2)
%% INPUT: two crossing tracts (AFQ)
%% Number Name Full Name
% 1 Thal_Rad_L Left Thalamic Radiation
% 2 Thal_Rad_R Right Thalamic Radiation
% 3 CST_L Left Corticospinal
% 4 CST_R Right Corticospinal
% 5 Cing_L Left Cingulum Cingulate
% 6 Cing_R Right Cingulum Cingulate
% 7 Hipp_L Left Cingulum Hippocampus
% 8 Hipp_R Right Cingulum Hippocampus
% 9 Call_Maj Callosum Forceps Major
% 10 Call_Min Callosum Forceps Minor
% 11 IFOF_L Left IFOF
% 12 IFOF_R Right IFOF
% 13 ILF_L Left ILF
% 14 ILF_R Right ILF
% 15 SLF_L Left SLF
% 16 SLF_R Right SLF
% 17 Unc_L Left Uncinate
% 18 Unc_R Right Uncinate
% 19 ARC_L Left Arcuate
% 20 ARC_R Right Arcuate
%% INPUT: two crossing tracts (Dan tracts)
%% Number Name Full Name
% 1 Thal_Rad_L Left Thalamic Radiation
% 2 Thal_Rad_R Right Thalamic Radiation
% 3 CST_L Left Corticospinal
% 4 CST_R Right Corticospinal
% 5 Cing_L Left Cingulum Cingulate
% 6 Cing_R Right Cingulum Cingulate
% 7 Hipp_L Left Cingulum Hippocampus
% 8 Hipp_R Right Cingulum Hippocampus
% 9 Call_Maj Callosum Forceps Major
% 10 Call_Min Callosum Forceps Minor
% 11 IFOF_L Left IFOF
% 12 IFOF_R Right IFOF
% 13 Unc_L Left Uncinate
% 14 Unc_R Right Uncinate
% 15 ARC_L Left Arcuate
% 16 ARC_R Right Arcuate
% 17 VOF_L Left VOF
% 18 VOF_R Right VOF
% 19 pARC_L Left pArc
% 20 pARC_R Right pArc
% 21 TPC_L Left TPC
% 22 TPC_R Right TPC
% 23 MdLF-SPL_L Left MdLF-SPL
% 24 MdLF-SPL_R Right MdLF-SPL
% 25 MdLF-Ang_L Left MdLF-Ang
% 26 MdLF-Ang_R Right MdLF-Ang
% 27 Meyer_L Left Meyer
% 28 Meyer_R Right Meyer
% 29 Baum_L Left Baum
% 30 Baum_R Right Baum
% 31 SLF1_L Left SLF1
% 32 SLF1_R Right SLF1
% 33 SLF2_L Left SLF2
% 34 SLF2_R Right SLF2
% 35 SLF3_L Left SLF3
% 36 SLF3_R Right SLF3
% 37 ILF_L Left ILF
% 38 ILF_R Right ILF
%% Get tract numbers
other_tract_number = [];
if info.segmentation_type == 'AFQ'
tract_number_1 = Get_tract_number(tract_name_1);
tract_number_2 = Get_tract_number(tract_name_2);
else
tract_number_1 = Get_tract_number_Dan(tract_name_1);
tract_number_2 = Get_tract_number_Dan(tract_name_2);
end
%% Set the Path for the output
dataOutputPath = info.output.niftis;
%% load fe structure
FileName = info.input.optimal;
load(FileName);
dwiFile = info.input.dwi_path;
%% Generate nifti for original data
ni = niftiRead(dwiFile);
%% Load classification file
load(info.input.classification_path);
%% Generate niftis for single tracts prediction
tract_set = 1:20; % AFQ has 20 tracts (this must be updated for using Dan segmentation)
tract_set = tract_set(tract_set~=tract_number_1 & tract_set~=tract_number_2);
for i=1:length(tract_set)
tract_name = Get_tract_name(tract_set(i));
disp(tract_name)
Gen_nifti_single_tract(fe,classification,tract_set(i),tract_name, dataOutputPath, ni, info)
end
end
function [] = Gen_nifti_single_tract(fe,classification,tract,fgName,dataOutputPath,ni,info)
name = fullfile(dataOutputPath,strcat(fgName,'.nii.gz'));
coords = fe.roi.coords; % Get the coordinates of the nodes in each voxel of the connectome
dwi = dwiLoad(info.input.dwi_path); % load dwi structure
fibers = find(classification.index == tract);
diff_signal = feGet(fe,'pred tract',fibers);
diff_signal(diff_signal==0) = NaN;
Generate_nifti(ni,name,coords,dwi,diff_signal);
end
function [] = Gen_nifti_crossing_tracts(fe,classification,tract1,tract2,other_tract_number,fgName,dataOutputPath,ni,info)
name = fullfile(dataOutputPath,strcat(fgName,'.nii.gz'));
coords = fe.roi.coords; % Get the coordinates of the nodes in each voxel of the connectome
dwi = dwiLoad(info.input.dwi_path); % load dwi structure
fibers1 = find(classification.index == tract1);
fibers2 = find(classification.index == tract2);
fibers = [fibers1; fibers2];
for i=1:length(other_tract_number)
fibers = [fibers ;find(classification.index == other_tract_number(i))];
end
diff_signal = feGet(fe,'pred tract',fibers);
diff_signal(diff_signal==0) = NaN;
Generate_nifti(ni,name,coords,dwi,diff_signal);
end
function [] = Generate_nifti(ni_in,name,coords,dwi,dwisignal)
ni_out = ni_in;
ni_out.fname = name;
bvals = dwi.bvals;
indexes = find(bvals~=0);
b0indexes = find(bvals==0);
% Copy original S0 values
b0_data = nan(size(b0indexes,1),size(coords,1));
for ivx = 1:size(coords,1)
b0_data(:,ivx) = ni_out.data(coords(ivx,1),coords(ivx,2),coords(ivx,3),b0indexes);
end
ni_out.data = nan(size(ni_in.data));
% Replace Nans with b0_data
ni_out.data = feReplaceImageValues(ni_out.data,b0_data,coords,b0indexes);
% Replace Nans with dw_vals
ni_out.data = feReplaceImageValues(ni_out.data,dwisignal,coords,indexes);
% save nifti to disk
niftiWrite(ni_out,ni_out.fname);
end