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B_preprocessing.m
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B_preprocessing.m
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function B_preprocessingV2
% Contains all preprocessing steps (except centering the origin, which is
% handled by dicom2nifti) for fbb-skull investigation
% Housekeeping constants)
SCRIPT_LOCATION = fileparts(mfilename("fullpath"));
BASE_DIR = fullfile(SCRIPT_LOCATION, "..");
DATA_DIR = fullfile(BASE_DIR, 'data');
SPM_DIR = fileparts(which('spm'));
PET_DIR_TEMPL = 'pet'; % single quotes --> char --> indexable
CT_DIR_TEMPL = 'ct';
% CT names
CT_TEMPL = 'ct01.nii';
WCT_TEMPL = 'wct01.nii';
MEAN_CT_TEMPL = 'mean_ct.nii';
MEAN_CT_SKULL_TEMPL = 'mean_ct_skull.nii';
iwMEAN_CT_SKULL_TEMPL = 'iwmean_ct_skull.nii';
CT_SKULLmeanCT750_TEMPLATE = 'ct01_skullmeanCT750';
CT_SKULLTPM_TEMPL = 'ct01_skullTPM.nii';
CT_SKULLTPMb05_TEMPL = 'ct01_skullTPMb05.nii';
% PET names
PET_TEMPL = 'pet01.nii';
PET_SKULL_TEMPL = 'pet01_skull.nii';
WPET_TEMPL = 'wpet01.nii';
WPET_PONS_TEMPL = 'wpet01_pons.nii';
CENTILOID_PET_TEMPL = 'centiloidpet01.nii';
CENTILOID_PET_SKULL_TEMPL = 'centiloidpet01_skull.nii';
PET_SKULLmeanCT750_TEMPLATE = 'pet01_skullmeanCT750';
PET_SKULLTPM_TEMPL = 'pet01_skullTPM.nii';
PET_SKULLTPMb05_TEMPL = 'pet01_skullTPMb05.nii';
% Masks
MNI_PONS_MASK = fullfile(DATA_DIR, "voi_Pons_2mm.nii");
% Mean CT
MEAN_CT = fullfile(DATA_DIR, MEAN_CT_TEMPL);
MEAN_CT_SKULL = fullfile(DATA_DIR, MEAN_CT_SKULL_TEMPL);
iwMEAN_CT_SKULL = fullfile(DATA_DIR, iwMEAN_CT_SKULL_TEMPL);
% Flowfields
ns2MNI_TEMPLATE = strcat('y_', CT_TEMPL);
MNI2ns_TEMPLATE = strcat('iy_', CT_TEMPL);
% TPMs
spm_TPM_skull = fullfile(SPM_DIR, 'tpm', 'TPM.nii,4');
iw_TPM_TEMPLATE = 'iwTPM.nii';
iw_TPMb05_TEMPLATE = 'iwTPMb05.nii';
iw_spm_TPM_skull = fullfile(SPM_DIR, 'tpm', iw_TPM_TEMPLATE);
% Collect patient file
PATIENT_FILE = fullfile(BASE_DIR, "patients.mat");
load(PATIENT_FILE, "patients");
SUBS = 1:44;
% Settings
debug = 0;
% First batch
do_clean_CT = 1;
do_coreg = 1; % CT to PET
do_seg = 1; % CT
do_norm = 1; % CT and PET to MNI
do_pons_mask = 1; % apply MNI pons to warped PET
do_iwarp_TPM = 1; % warp tpm to native space and generate binarized TPM
% Mean CT generation (CAVE: This requires the first batch to be done AND is
% required by the second batch modules. has to run before the second batch
% modules)
do_meanCT = 0; % generate mean CT
% Second batch (CAVE: This requires the first batch to be done AND the
% meanCT generation to be done as well)
do_TPM_mask = 0; % apply warped TPM and warped binarized TPM to PET and CT
do_iwarp_meanCT = 0; % warp the meanCT to respective patient space. CAVE:
do_meanCT_mask = 0; % apply the warped meanCT to respective PET and CT
% Loop over subjects
for i = 1:numel(SUBS)
% Reset matlabbatch
matlabbatch = [];
mbi = 0;
% Define subject specific paths
sub = SUBS(i);
sub_dir = fullfile(DATA_DIR, patients.folder(sub));
fprintf("Preparing first batch for %s\n... ", sub_dir);
ct_dir = fullfile(sub_dir, CT_DIR_TEMPL);
pet_dir = fullfile(sub_dir, PET_DIR_TEMPL);
ct = fullfile(ct_dir, CT_TEMPL);
ct_skullTPM = fullfile(ct_dir, CT_SKULLTPM_TEMPL);
ct_skullTPMb05 = fullfile(ct_dir, CT_SKULLTPMb05_TEMPL);
ct_skullmeanCT750 = fullfile(ct_dir, CT_SKULLmeanCT750_TEMPLATE);
mean_ct_skull_mask = fullfile(ct_dir, iwMEAN_CT_SKULL_TEMPL);
pet = fullfile(pet_dir, PET_TEMPL);
pet_skull = fullfile(pet_dir, PET_SKULL_TEMPL);
pet_skullTPM = fullfile(pet_dir, PET_SKULLTPM_TEMPL);
pet_skullTPMb05 = fullfile(pet_dir, PET_SKULLTPMb05_TEMPL);
pet_skullmeanCT750 = fullfile(pet_dir, PET_SKULLmeanCT750_TEMPLATE);
wpet = fullfile(pet_dir, WPET_TEMPL);
wpet_pons = fullfile(pet_dir, WPET_PONS_TEMPL);
centiloid_pet = fullfile(pet_dir, CENTILOID_PET_TEMPL);
centiloid_pet_skull = fullfile(pet_dir, CENTILOID_PET_SKULL_TEMPL);
iw_tpm = fullfile(sub_dir, iw_TPM_TEMPLATE);
iw_tpmb05 = fullfile(sub_dir, iw_TPMb05_TEMPLATE);
ns2MNI_flowfield = fullfile(ct_dir, ns2MNI_TEMPLATE);
MNI2ns_flowfield = fullfile(ct_dir, MNI2ns_TEMPLATE);
bb = spm_get_bbox(char(pet)); % this defines the bbox of our warp targets
% Clean low dose CT (get rid of outside low density structures as suggested in Presotto
% et al. 2018) and apply PET BBox to CT
if do_clean_CT
hdr = spm_vol(char(ct));
vols = spm_read_vols(hdr);
% ==========================================
vols(vols < -300) = -1024;
% ==========================================
spm_write_vol(hdr, vols);
resize_img(char(ct), [nan nan nan], bb);
end
% Coregistration (coregister CT to PET)
if do_coreg
mbi = mbi + 1;
matlabbatch{mbi}.spm.spatial.coreg.estimate.ref = cellstr(pet);
matlabbatch{mbi}.spm.spatial.coreg.estimate.source = cellstr(ct);
matlabbatch{mbi}.spm.spatial.coreg.estimate.other = {''};
matlabbatch{mbi}.spm.spatial.coreg.estimate.eoptions.cost_fun = 'nmi';
matlabbatch{mbi}.spm.spatial.coreg.estimate.eoptions.sep = [4 2];
matlabbatch{mbi}.spm.spatial.coreg.estimate.eoptions.tol = [0.02 0.02 0.02 0.001 0.001 0.001 0.01 0.01 0.01 0.001 0.001 0.001];
matlabbatch{mbi}.spm.spatial.coreg.estimate.eoptions.fwhm = [7 7];
end
% Segment CT and obtain forward and backwards transformations
if do_seg
mbi = mbi + 1;
matlabbatch{mbi}.spm.spatial.preproc.channel.vols = cellstr(ct);
matlabbatch{mbi}.spm.spatial.preproc.channel.biasreg = 0;
matlabbatch{mbi}.spm.spatial.preproc.channel.biasfwhm = 60;
matlabbatch{mbi}.spm.spatial.preproc.channel.write = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(1).tpm = {'/home/noah/spm12/tpm/TPM.nii,1'};
matlabbatch{mbi}.spm.spatial.preproc.tissue(1).ngaus = 1;
matlabbatch{mbi}.spm.spatial.preproc.tissue(1).native = [1 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(1).warped = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(2).tpm = {'/home/noah/spm12/tpm/TPM.nii,2'};
matlabbatch{mbi}.spm.spatial.preproc.tissue(2).ngaus = 1;
matlabbatch{mbi}.spm.spatial.preproc.tissue(2).native = [1 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(2).warped = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(3).tpm = {'/home/noah/spm12/tpm/TPM.nii,3'};
matlabbatch{mbi}.spm.spatial.preproc.tissue(3).ngaus = 2;
matlabbatch{mbi}.spm.spatial.preproc.tissue(3).native = [1 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(3).warped = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(4).tpm = {'/home/noah/spm12/tpm/TPM.nii,4'};
matlabbatch{mbi}.spm.spatial.preproc.tissue(4).ngaus = 2;
matlabbatch{mbi}.spm.spatial.preproc.tissue(4).native = [1 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(4).warped = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(5).tpm = {'/home/noah/spm12/tpm/TPM.nii,5'};
matlabbatch{mbi}.spm.spatial.preproc.tissue(5).ngaus = 2;
matlabbatch{mbi}.spm.spatial.preproc.tissue(5).native = [1 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(5).warped = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(6).tpm = {'/home/noah/spm12/tpm/TPM.nii,6'};
matlabbatch{mbi}.spm.spatial.preproc.tissue(6).ngaus = 2;
matlabbatch{mbi}.spm.spatial.preproc.tissue(6).native = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.tissue(6).warped = [0 0];
matlabbatch{mbi}.spm.spatial.preproc.warp.mrf = 1;
matlabbatch{mbi}.spm.spatial.preproc.warp.cleanup = 1;
matlabbatch{mbi}.spm.spatial.preproc.warp.reg = [0 0.001 0.5 0.05 0.2];
matlabbatch{mbi}.spm.spatial.preproc.warp.affreg = 'mni';
matlabbatch{mbi}.spm.spatial.preproc.warp.fwhm = 0;
matlabbatch{mbi}.spm.spatial.preproc.warp.samp = 3;
matlabbatch{mbi}.spm.spatial.preproc.warp.write = [1 1];
matlabbatch{mbi}.spm.spatial.preproc.warp.vox = NaN;
matlabbatch{mbi}.spm.spatial.preproc.warp.bb = [NaN NaN NaN;NaN NaN NaN];
end
% Normalization (use forward flow field from segmentation)
if do_norm
mbi = mbi + 1;
matlabbatch{mbi}.spm.spatial.normalise.write.subj.def = cellstr(ns2MNI_flowfield);
matlabbatch{mbi}.spm.spatial.normalise.write.subj.resample = cellstr([ct; pet]);
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.bb = bb; %[-90 -126 -72; 90 90 108]; % derived from TPM
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.vox = [1.5 1.5 1.5]; % derived from TPM
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.interp = 4;
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.prefix = 'w';
end
% Apply MNI pons mask to normalized PET
if do_pons_mask
mbi = mbi + 1;
matlabbatch{mbi}.spm.util.imcalc.input = cellstr([wpet; MNI_PONS_MASK]);
matlabbatch{mbi}.spm.util.imcalc.output = char(wpet_pons);
matlabbatch{mbi}.spm.util.imcalc.outdir = cellstr(pet_dir);
matlabbatch{mbi}.spm.util.imcalc.expression = 'i1.*i2';
matlabbatch{mbi}.spm.util.imcalc.var = struct('name', {}, 'value', {});
matlabbatch{mbi}.spm.util.imcalc.options.dmtx = 0;
matlabbatch{mbi}.spm.util.imcalc.options.mask = 0;
matlabbatch{mbi}.spm.util.imcalc.options.interp = 1;
matlabbatch{mbi}.spm.util.imcalc.options.dtype = 4;
end
% Warp skull TPM to patient space using backwards transformation
if do_iwarp_TPM
mbi = mbi + 1;
matlabbatch{mbi}.spm.spatial.normalise.write.subj.def = cellstr(MNI2ns_flowfield);
matlabbatch{mbi}.spm.spatial.normalise.write.subj.resample = cellstr(spm_TPM_skull); % 4th frame of TPM --> skull
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.bb = bb; %[-90 -126 -72; 90 90 108]; % derived from TPM
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.vox = [1.5 1.5 1.5]; % derived from TPM
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.interp = 4;
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.prefix = 'iw'; % inverse warped
end
% run batch
save("matlabbatch1.mat", "matlabbatch");
if ~debug && ~isempty(matlabbatch)
spm_jobman('initcfg');
spm_jobman('run',matlabbatch);
end
% Reset batch
matlabbatch = [];
mbi = 0;
% move iw_TPM from SPM12 to sub_folder
if do_iwarp_TPM
cmd = sprintf('mv %s %s -v', iw_spm_TPM_skull, iw_tpm);
system(cmd);
end
% Binarize TPM in patient space
if do_iwarp_TPM
mbi = mbi + 1;
matlabbatch{mbi}.spm.util.imcalc.input = cellstr(strcat(iw_tpm, ',4'));
matlabbatch{mbi}.spm.util.imcalc.output = char(iw_tpmb05); % has only one frame
matlabbatch{mbi}.spm.util.imcalc.outdir = cellstr(sub_dir);
matlabbatch{mbi}.spm.util.imcalc.expression = 'i1>0.5';
matlabbatch{mbi}.spm.util.imcalc.var = struct('name', {}, 'value', {});
matlabbatch{mbi}.spm.util.imcalc.options.dmtx = 0;
matlabbatch{mbi}.spm.util.imcalc.options.mask = 0;
matlabbatch{mbi}.spm.util.imcalc.options.interp = 1;
matlabbatch{mbi}.spm.util.imcalc.options.dtype = 4;
end
% Apply TPM and binarized TPM to PET and CT
if do_TPM_mask
mbi = mbi + 1;
matlabbatch{mbi}.spm.util.imcalc.input = cellstr([strcat(iw_tpm,',4') ct]');
matlabbatch{mbi}.spm.util.imcalc.output = char(ct_skullTPM);
matlabbatch{mbi}.spm.util.imcalc.outdir = cellstr(ct_dir); % will be ignored
matlabbatch{mbi}.spm.util.imcalc.expression = 'i1.*i2'; % so we dont get weird negative values
matlabbatch{mbi}.spm.util.imcalc.var = struct('name', {}, 'value', {});
matlabbatch{mbi}.spm.util.imcalc.options.dmtx = 0;
matlabbatch{mbi}.spm.util.imcalc.options.mask = 0;
matlabbatch{mbi}.spm.util.imcalc.options.interp = 1;
matlabbatch{mbi}.spm.util.imcalc.options.dtype = 4;
mbi = mbi + 1;
matlabbatch{mbi} = matlabbatch{mbi-1};
matlabbatch{mbi}.spm.util.imcalc.input = cellstr([iw_tpmb05 ct]');
matlabbatch{mbi}.spm.util.imcalc.output = char(ct_skullTPMb05);
mbi = mbi + 1;
matlabbatch{mbi} = matlabbatch{mbi-1};
matlabbatch{mbi}.spm.util.imcalc.input = cellstr([strcat(iw_tpm,',4') pet]');
matlabbatch{mbi}.spm.util.imcalc.output = char(pet_skullTPM);
matlabbatch{mbi}.spm.util.imcalc.expression = 'i1.*i2';
mbi = mbi + 1;
matlabbatch{mbi} = matlabbatch{mbi-1};
matlabbatch{mbi}.spm.util.imcalc.input = cellstr([iw_tpmb05 pet]');
matlabbatch{mbi}.spm.util.imcalc.output = char(pet_skullTPMb05);
matlabbatch{mbi}.spm.util.imcalc.expression = 'i1.*i2';
end
% Warp mean CT skull mask to patient space
if do_iwarp_meanCT
mbi = mbi + 1;
matlabbatch{mbi}.spm.spatial.normalise.write.subj.def = cellstr(MNI2ns_flowfield);
matlabbatch{mbi}.spm.spatial.normalise.write.subj.resample = cellstr(MEAN_CT_SKULL);
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.bb = bb; %[-90 -126 -72; 90 90 108]; % derived from TPM
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.vox = [1.5 1.5 1.5]; % derived from TPM
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.interp = 4;
matlabbatch{mbi}.spm.spatial.normalise.write.woptions.prefix = 'iw'; % inverse warped
end
% run batch
save("matlabbatch2.mat", "matlabbatch");
if ~debug && ~isempty(matlabbatch)
spm_jobman('initcfg');
spm_jobman('run',matlabbatch);
end
% Reset batch
matlabbatch = [];
mbi = 0;
% move warped meanCT to subject folder
if do_iwarp_meanCT
cmd = sprintf('mv %s %s -v', iwMEAN_CT_SKULL, mean_ct_skull_mask);
system(cmd);
end
% Apply meanCT skull mask to PET and CT
if do_meanCT_mask
mbi = mbi + 1;
matlabbatch{mbi}.spm.util.imcalc.input = cellstr([mean_ct_skull_mask ct]');
matlabbatch{mbi}.spm.util.imcalc.output = char(ct_skullmeanCT750);
matlabbatch{mbi}.spm.util.imcalc.outdir = cellstr(ct_dir); % will be ignored
matlabbatch{mbi}.spm.util.imcalc.expression = 'i1.*i2';
matlabbatch{mbi}.spm.util.imcalc.var = struct('name', {}, 'value', {});
matlabbatch{mbi}.spm.util.imcalc.options.dmtx = 0;
matlabbatch{mbi}.spm.util.imcalc.options.mask = 0;
matlabbatch{mbi}.spm.util.imcalc.options.interp = 1;
matlabbatch{mbi}.spm.util.imcalc.options.dtype = 4;
mbi = mbi + 1;
matlabbatch{mbi} = matlabbatch{mbi-1};
matlabbatch{mbi}.spm.util.imcalc.input = cellstr([mean_ct_skull_mask pet]'); % use MNI masks to define vox size etc.
matlabbatch{mbi}.spm.util.imcalc.output = char(pet_skullmeanCT750);
end
% run batch
save("matlabbatch1.mat", "matlabbatch");
if ~debug && ~isempty(matlabbatch)
spm_jobman('initcfg');
spm_jobman('run',matlabbatch);
end
% Reset batch
fprintf("done.\n\n");
matlabbatch = [];
mbi = 0;
end
% Create mean CT
if do_meanCT
matlabbatch = [];
all_wCTs = [];
% Collect all warped CTs
for i = 1:numel(SUBS)
sub = SUBS(i);
sub_dir = fullfile(DATA_DIR, patients.folder(sub));
wct = char(fullfile(sub_dir, 'ct', WCT_TEMPL));
all_wCTs = char(all_wCTs, wct);
end
fprintf("\nCollected %d wCTs\n", size(all_wCTs,1));
% Calculate the mean
matlabbatch{1}.spm.util.imcalc.input = cellstr(all_wCTs);
matlabbatch{1}.spm.util.imcalc.output = char(MEAN_CT);
matlabbatch{1}.spm.util.imcalc.outdir = cellstr(DATA_DIR);
matlabbatch{1}.spm.util.imcalc.expression = 'mean(X)';
matlabbatch{1}.spm.util.imcalc.var = struct('name', {}, 'value', {});
matlabbatch{1}.spm.util.imcalc.options.dmtx = 1;
matlabbatch{1}.spm.util.imcalc.options.mask = 0;
matlabbatch{1}.spm.util.imcalc.options.interp = 1;
matlabbatch{1}.spm.util.imcalc.options.dtype = 4;
% Obtain skull mask from mean CT
matlabbatch{2}.spm.util.imcalc.input = cellstr(MEAN_CT);
matlabbatch{2}.spm.util.imcalc.output = char(MEAN_CT_SKULL);
matlabbatch{2}.spm.util.imcalc.outdir = cellstr(sub_dir);
matlabbatch{2}.spm.util.imcalc.expression = 'i1>750';
matlabbatch{2}.spm.util.imcalc.var = struct('name', {}, 'value', {});
matlabbatch{2}.spm.util.imcalc.options.dmtx = 0;
matlabbatch{2}.spm.util.imcalc.options.mask = 0;
matlabbatch{2}.spm.util.imcalc.options.interp = 1;
matlabbatch{2}.spm.util.imcalc.options.dtype = 4;
% run batch
save("matlabbatch1.mat", "matlabbatch");
if ~debug && ~isempty(matlabbatch)
spm_jobman('initcfg');
spm_jobman('run',matlabbatch);
end
end