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danlurie/backnorm.m

Created April 1, 2019 21:21
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backnorm.m
function [outputBnormFiles] = backNormROI(structuralImage,outputSpaceImage,toBackNormROIs,outputPrefix,outputDirectory,varargin)
% INPUTS:
% structuralDirectory - directory for structural - generate norm files here
% structuralImage - image that will be normalized
% meanEpiFile - image for the mean of the functionals
% preprocessingDirectory - make a directory for the backNormROIs
% toBackNormROIs - images that will be backnormalized
% assume MNI spaces
% outputPrefix - append this prefix to the backNormROIs
%
% OPTIONAL INPUTS:
% restart = 1/0 default is 0, this will delete any existing ROIs
%
% FLOW OF SCRIPTS
% 1. Normalize the structural image
% generate norm and inverse norm parameters
%
% 2. Back-normalize the Atlas ROIs into structural space
%
% 3. Binarize the Atlas ROI in structural space
%
% 4. Resample the ROI from Structural into EPI space
%
% OPTIONAL INPUTS
if length(varargin)>=1
restart = varargin{1};
else
restart = 0;
end
% Number of ROIs to be back-normalized
numROIs = length(toBackNormROIs);
outputBnormFiles = cell(1,numROIs);
% ROIs saved in sub directory within structural directory
[structuralDirectory,~,~] = fileparts(structuralImage);
structuralDirectory = [structuralDirectory '/'];
%% Step 1: estimate the noramlization of the structural image
% get the inverse normalization estimate as well
inverseDeformPrefix = 'iy_';
inverseDeformationFndr = dir([structuralDirectory inverseDeformPrefix '*']);
if isempty(inverseDeformationFndr)
fprintf('Running Segmentation\n');
clear matlabbatch
spm_jobman('initcfg');
toSegmentStructFile = dir([structuralDirectory 'ons*.nii']);
if isempty(toSegmentStructFile)
toSegmentStructFile = dir([structuralDirectory 'sub*.nii']);
end
matlabbatch{1}.spm.spatial.preproc.channel(1).vols = {[structuralDirectory toSegmentStructFile(1).name]};
% mean bias corrected image is written out
matlabbatch{1}.spm.spatial.preproc.channel.write = [0 1];
% change defaults to generate [inverse forward] normalization
matlabbatch{1}.spm.spatial.preproc.warp.write = [1 1];
spm_jobman('run',matlabbatch);
inverseDeformationFndr = dir([structuralDirectory inverseDeformPrefix '*']);
end
inverseDeformationFile = [structuralDirectory inverseDeformationFndr(1).name];
%% STEP 2: Apply inverse normalization
for roiIdx = 1:numROIs
toBnormFile = toBackNormROIs{roiIdx};
[~,fileName,ext]=fileparts(toBnormFile);
outputFile = [outputDirectory outputPrefix fileName ext];
outputBnormFiles{roiIdx} = outputFile;
if restart && exist(outputFile,'file')==2
delete(outputFile);
end
if exist(outputFile,'file')~=2
clear matlabbatch
spm_jobman('initcfg');
matlabbatch{1}.spm.util.defs.comp{1}.inv.comp{1}.def = {inverseDeformationFile};
matlabbatch{1}.spm.util.defs.comp{1}.inv.space = {structuralImage};
matlabbatch{1}.spm.util.defs.out{1}.push.fnames = {toBnormFile};
matlabbatch{1}.spm.util.defs.out{1}.push.weight = {''};
matlabbatch{1}.spm.util.defs.out{1}.push.savedir.saveusr = {outputDirectory};
matlabbatch{1}.spm.util.defs.out{1}.push.fov.file = {outputSpaceImage};
matlabbatch{1}.spm.util.defs.out{1}.push.preserve = 0;
matlabbatch{1}.spm.util.defs.out{1}.push.fwhm = [0 0 0];
spm_jobman('run',matlabbatch);
fprintf('Done\n')
movefile([outputDirectory 'w' fileName ext],outputFile);
end
end
end
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