From 602ed4215a43b67d45c256993066cc921c202865 Mon Sep 17 00:00:00 2001
From: rjpuzniak <rjpuzniak@gmail.com>
Date: Fri, 3 Mar 2017 16:11:20 +0100
Subject: [PATCH 1/7] Create 00_fsl_preprocess.sh

---
 00_fsl_preprocess.sh | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 00_fsl_preprocess.sh

diff --git a/00_fsl_preprocess.sh b/00_fsl_preprocess.sh
new file mode 100644
index 0000000..d4ea38c
--- /dev/null
+++ b/00_fsl_preprocess.sh
@@ -0,0 +1 @@
+#sth

From ae8d5e0c1f95aecae90f31056ab86aac36bf40c6 Mon Sep 17 00:00:00 2001
From: franco <frakkopesto@gmail.com>
Date: Fri, 3 Mar 2017 16:38:50 +0100
Subject: [PATCH 2/7] Adding new file for temporaly pipeline

---
 testing_acpc.m => 01_testing_acpc.m |  0
 02_ensemble_tracking.txt            | 48 +++++++++++++++++++++++++++++
 03_life.m                           | 15 +++++++++
 3 files changed, 63 insertions(+)
 rename testing_acpc.m => 01_testing_acpc.m (100%)
 create mode 100644 02_ensemble_tracking.txt
 create mode 100644 03_life.m

diff --git a/testing_acpc.m b/01_testing_acpc.m
similarity index 100%
rename from testing_acpc.m
rename to 01_testing_acpc.m
diff --git a/02_ensemble_tracking.txt b/02_ensemble_tracking.txt
new file mode 100644
index 0000000..6d61b88
--- /dev/null
+++ b/02_ensemble_tracking.txt
@@ -0,0 +1,48 @@
+dwi2mask lw37_complete.mif lw37_mask.nii.gz	
+
+dwi2response tournier lw37_complete.mif -shell 1600 -lmax 8 -mask lw37_mask.nii.gz lw37_sfr.txt
+
+dwiextract lw37_complete.mif - | dwi2fod msmt_csd - lw37_sfr.txt lw37_fod.nii.gz -mask lw37_mask.nii.gz 
+
+# Get the 5TT image
+5ttgen fsl anatomy/t1_acpc.nii.gz lw_5tt.nii.gz
+
+# Generate tractogram
+
+FAs="0.05 0.10"
+Curv="60"
+
+for j in $FAs; do
+for k in $Curv; do
+tckgen lw37_fod.nii.gz lw_results_$j\_$k.tck -number 5000 -cutoff $j -angle $k -act lw_5tt.nii.gz -backtrack -seed_dynamic lw37_fod.nii.gz -unidirectional; 
+echo " "
+done
+done
+
+	
+	altogether=""
+
+	for z in lw_results*; do
+		altogether+="${z} "
+	done
+
+	tckedit $altogether lw_et.tck -force
+
+	# SIFT'em now to 9.6 mln
+	#tcksift ET_candidate.tck ../$i\_FOD.nii ET_candidate_sifted.tck -term_number 1000 -csv sifting_results.csv -force -info
+
+	# SIFT2 the results (maybe)
+
+	#tcksift2 ET_candidate_sifted.tck ../$i\_FOD.nii ET_candidate_sifted_weights -force
+
+	# Clear the folder
+	#rm results*
+	#rm ET_candidate.tck
+}
+
+for r in $subjects; do 
+  analizuj "$r"
+  done
+	
+
+
diff --git a/03_life.m b/03_life.m
new file mode 100644
index 0000000..6cc1558
--- /dev/null
+++ b/03_life.m
@@ -0,0 +1,15 @@
+
+% Build the file names for the diffusion data, the anatomical MRI.
+dwiFile       = fullfile('/media/auguser2016/Volume/Test','lw37_aligned_trilin.nii.gz');
+dwiFileRepeat = fullfile('/media/auguser2016/Volume/Test','lw37_aligned_trilin.nii.gz');
+t1File        = fullfile('/media/auguser2016/Volume/Test/anatomy','t1_acpc.nii.gz');
+fgFileName = fullfile('/media/auguser2016/Volume/Test','lw_et.tck')         
+
+% The final connectome and data astructure will be saved with this name:
+feFileName    = 'test_ensemble_tracking';
+
+L = 360; % Discretization parameter
+fe = feConnectomeInit(dwiFile,fgFileName,feFileName,[],dwiFileRepeat,t1File,L,[1,0]);
+
+Niter = 500;
+fe = feSet(fe,'fit',feFitModel(feGet(fe,'model'),feGet(fe,'dsigdemeaned'),'bbnnls',Niter,'preconditioner'));

From 16ac07766f495df389ea61ce767785838b6f8275 Mon Sep 17 00:00:00 2001
From: franco <frakkopesto@gmail.com>
Date: Fri, 3 Mar 2017 17:21:29 +0100
Subject: [PATCH 3/7] LiFE initial script

---
 03_life.m | 43 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 43 insertions(+)

diff --git a/03_life.m b/03_life.m
index 6cc1558..b11827d 100644
--- a/03_life.m
+++ b/03_life.m
@@ -13,3 +13,46 @@
 
 Niter = 500;
 fe = feSet(fe,'fit',feFitModel(feGet(fe,'model'),feGet(fe,'dsigdemeaned'),'bbnnls',Niter,'preconditioner'));
+
+% Remove non zero weighted fascicles
+fg = feGet(fe,'fibers acpc');
+w = feGet(fe,'fiber weights');
+positive_w = w > 0;
+fg = fgExtract(fg, positive_w, 'keep');
+
+% Use MBA to visualize
+colors     = {[.75 .25 .1]};
+viewCoords = [90,0];
+proportion_to_show = .05;
+threshold_length   = 10;
+slices     = {[18 0 0],[0 -40 0],[0 0 -14]}; % Values in mm from AC 
+
+% Prepare the plot of tract
+fg = rmfield(fg,'coordspace');
+
+% Pick a percentage of fascicles to display (the PN can be too dense for visualization).
+%fibs_indx = RandSample(1:length(fg.fibers),round(length(fg.fibers)*proportion_to_show));
+fg.fibers = fg.fibers(1:2000);
+
+% Display fascicles and anatomy
+fig_h = figure('name','Whole Brain','color','k');
+hold on
+
+% display anatomy
+t1 = niftiRead(t1File);
+%h  = mbaDisplayBrainSlice(t1, slices{1});
+%h  = mbaDisplayBrainSlice(t1, slices{2});
+
+% Disdplay fasciles
+set(gca,'visible','off','ylim',[-108 69],'xlim',[-75 75],'zlim',[-45 78],'Color','w')
+[~, light_h] = mbaDisplayConnectome(fg.fibers,fig_h,colors{1},'single');
+delete(light_h)
+view(viewCoords(1),viewCoords(2))
+light_h = camlight('right');
+lighting phong;
+%set(fig_h,'Units','normalized', 'Position',[0.5 .2 .4 .8]);
+set(gcf,'Color',[1 1 1])
+drawnow
+
+% save figure to disk
+print(fig_h,'my_figure','-dpng','-r600');%'-dpsc2')

From b74a9841a3d50fbbddd971b08da33eb59647d97c Mon Sep 17 00:00:00 2001
From: franco <frakkopesto@gmail.com>
Date: Mon, 13 Mar 2017 15:04:14 +0100
Subject: [PATCH 4/7] Script for general preprocessing using MRtrix and FSL.
 SFR and FOD is using single, default lmax value. In further steps multiple
 lmax values are used.

---
 00_fsl_preprocess.sh     | 118 ++++++++++++++++++++++++++++++++++++++-
 02_ensemble_tracking.txt |  75 +++++++++++++++----------
 03_life.m                |   2 +
 3 files changed, 164 insertions(+), 31 deletions(-)

diff --git a/00_fsl_preprocess.sh b/00_fsl_preprocess.sh
index d4ea38c..b8558eb 100644
--- a/00_fsl_preprocess.sh
+++ b/00_fsl_preprocess.sh
@@ -1 +1,117 @@
-#sth
+# Initializing
+
+# Folder with raw and preprocessed data
+data=/home/auguser2016/dMRI_DATA
+
+Preparation () {
+
+	# 2 resolutions (1.5 mm and 0.75mm), inside each folder all preprocessed data sets of corresponding resolution with masks, map of distortions etc.
+	a=${1::-6}
+	
+	low_res=PREPROCESSED_DATA/1.5mm_iso/$a
+	high_res=PREPROCESSED_DATA/0.75mm_iso/$a
+
+	mkdir $data/$low_res
+	mkdir $data/$low_res/Temporal
+	mkdir $data/$low_res/Temporal/Distortions
+
+	mkdir $data/$high_res
+	mkdir $data/$high_res/Temporal
+	
+	
+	cd $data/RAW_DATA/${1::-1}/s*/
+
+	# Raw data files - DWI and anatomy - unpacked with MRIcron (dcm2nii) as a 4D Nifti images. Raw data goes: RAW_DATA/data_set_name/study.../studies_X/ where important are those with ep2d
+	# Transforming Nifti into .mif files and denoising them. Denoising is the very first that should be done - it's results can be viewed.
+	
+	for b in *ep2d*; do
+		cd $b
+		mrconvert *a001.nii -stride -1,2,3,4 -fslgrad *.bvec *.bval $data/$low_res/Temporal/$a\_$b\.mif 
+		dwidenoise $data/$low_res/Temporal/$a\_$b.mif $data/$low_res/Temporal/$a\_$b\_denoised.mif -noise $data/$low_res/Temporal/Distortions/$a\_$b\_noise.mif -debug
+	  	cd ..
+	done
+
+	# Script from MRtrix interacting with fsl. Here version for correcting DWI with 2 phase encoding directions is used
+	dwipreproc AP  $data/$low_res/Temporal/*AP_denoised.mif -rpe_all $data/$low_res/Temporal/*PA_denoised.mif $data/$low_res/Temporal/$a\_denoised_preproc.mif -export_grad_mrtrix $data/$low_res/Temporal/Distortions/$a\_gradients 
+	
+	# Masking preprocessed data. Results should be checked
+	dwi2mask $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm_mask.mif
+
+	# Masked is used for bias field correction using ANTS software
+	dwibiascorrect -ants $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm.mif -mask $data/$low_res/$a\_clean_150mm_mask.mif -bias $data/$low_res/Temporal/Distortions/$a\_bias_field.mif
+ 
+	# Preprocessing of 1.5 mm iso data sets done. Moving to upsampled resolution
+	
+	# Upsampling by factor of 2 to 0.75mm. Justified step, in FBA even factor 3 can be recommended
+	mrresize $data/$low_res/$a\_clean_150mm.mif -scale 2.0 $data/$high_res/$a\_clean_075mm.mif
+	
+	# Calculating mask again
+	dwi2mask $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Estimating single fibre response (SFR) for default lmax
+	dwi2response tournier $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_SFR.txt -shell 1600 -lmax 8 -mask $data/$high_res/$a\_clean_075mm_mask.mif -voxels $data/$high_res/Temporal/$a_clean_075mm_SFR_voxels.mif
+
+	# Estimating FOD for previously obtained SFR
+	dwiextract $data/$high_res/$a\_clean_075mm.mif - | dwi2fod msmt_csd - $data/$high_res/$a\_clean_075mm_SFR.txt $data/$high_res/$a\_clean_075mm_FOD.mif -mask $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Performing coregistration of anatomical image to DWI images and segmenting it. It's easier approach as gradient table is not rotated this way. However for cross-modal studies it would be better to register DWI to anatomy
+
+	cd *MPRAGE*iso
+	
+	# Converting DWI image from .mif to .nii.gz as FSL likes. This step should be checked as well.
+	mrconvert $data/$high_res/$a\_clean_075mm.mif $data/$high_res/Temporal/$a\_clean_075mm.nii.gz
+	
+	# Coping anatomical image to corresponding folder
+	cp o* $data/$high_res/$a\_anatomical.nii.gz
+
+	# Extracting clean brain from anatomical image. Check this step
+	bet2 $data/$high_res/$a\_anatomical.nii.gz $data/$high_res/Temporal/$a\_anatomical_brain.nii.gz -f 0.6  	
+	
+	# Corregister DWI to anatomy
+	epi_reg --epi=$data/$high_res/Temporal/$a\_clean_075mm.nii.gz --t1=$data/$high_res/$a\_anatomical.nii.gz --t1brain=$data/$high_res/Temporal/$a\_anatomical_brain.nii.gz --out=$data/$high_res/Temporal/$a\_nodif2mprage_2 --echospacing=0.00023 --pedir=-y
+
+	# Reverse corregistration matrix
+	convert_xfm -inverse $data/$high_res/Temporal/$a\_nodif2mprage_2.mat -omat $data/$high_res/Temporal/$a\_mprage2nodif_2.mat
+
+	# Apply reverted matrix to corregister anatomy to DWI
+	flirt -in $data/$high_res/$a\_anatomical.nii.gz -ref $data/$high_res/Temporal/$a\_clean_075mm.nii.gz -out $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2 -applyxfm -init $data/$high_res/Temporal/$a\_mprage2nodif_2.mat -interp sinc -sincwidth 7 -sincwindow hanning
+
+	# Perform segmentation into WM, GM, subcortical GM, CSF and possible pathological tissue using FIRST from FSL
+	5ttgen fsl $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2.nii.gz $data/$high_res/$a\_075mm_5tt.nii.gz
+
+}
+
+cd $data/RAW_DATA
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+#list=(fe21_1325/)
+
+# This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
+
+for i in ${list[@]:0:3}; do Preparation $i & done
+wait
+for i in ${list[@]:3:6}; do Preparation $i & done
+wait
+for i in ${list[@]:6:9}; do Preparation $i & done
+wait
+for i in ${list[@]:9:12}; do Preparation $i & done
+wait
+for i in ${list[@]:12:15}; do Preparation $i & done
+wait
+for i in ${list[@]:15:18}; do Preparation $i & done
+wait
+for i in ${list[@]:18:21}; do Preparation $i & done
+wait
+for i in ${list[@]:21:24}; do Preparation $i & done
+wait
+for i in ${list[@]:24:27}; do Preparation $i & done
+wait
+for i in ${list[@]:27:30}; do Preparation $i & done
+wait
+for i in ${list[@]:30:33}; do Preparation $i & done
+wait
+
+# Returning to original folder
+cd /home/auguser2016/Scripts/
+
diff --git a/02_ensemble_tracking.txt b/02_ensemble_tracking.txt
index 6d61b88..c5223eb 100644
--- a/02_ensemble_tracking.txt
+++ b/02_ensemble_tracking.txt
@@ -1,48 +1,63 @@
-dwi2mask lw37_complete.mif lw37_mask.nii.gz	
+# 1 Argument: ID of participant
 
-dwi2response tournier lw37_complete.mif -shell 1600 -lmax 8 -mask lw37_mask.nii.gz lw37_sfr.txt
+# Requirements:
+# Data preprocessed
+# DWI corregisterd to anatomy
+# Masks estimated
+# ROIs drawn
 
-dwiextract lw37_complete.mif - | dwi2fod msmt_csd - lw37_sfr.txt lw37_fod.nii.gz -mask lw37_mask.nii.gz 
+subj=$1
+analysis_folder=/media/auguser2016/Volume/Quantifying_Chiasm
 
-# Get the 5TT image
-5ttgen fsl anatomy/t1_acpc.nii.gz lw_5tt.nii.gz
+mkdir $analysis_folder/$subj
 
-# Generate tractogram
+output=$analysis_folder/$subj
 
-FAs="0.05 0.10"
-Curv="60"
+# SFR Estimation
+lmax=6 'This should be as low as possible, optimal for most participants value #SFR for lower lmax, keep it and use higher 8,10,12 for fod estimation OR Get SFR with optimal lmax for most participants and use given lmax for all participants. Lower lmax preffered'
+dwi2response tournier $subj\_complete.mif -shell 1600 -lmax $lmax -mask $subj\_mask_upsampled.nii.gz $output/$subj\_sfr.txt 
 
-for j in $FAs; do
-for k in $Curv; do
-tckgen lw37_fod.nii.gz lw_results_$j\_$k.tck -number 5000 -cutoff $j -angle $k -act lw_5tt.nii.gz -backtrack -seed_dynamic lw37_fod.nii.gz -unidirectional; 
-echo " "
-done
+# Estimation of Fiber Orientation Distribution function
+for lmax in "8 10 12"; do  
+  dwiextract $subj\_complete.mif - | dwi2fod msmt_csd - $output/$subj\_sfr.txt $output/$subj\_fod_lmax_$lmax\.nii.gz -mask $subj\_mask_upsampled.nii.gz -lmax $lmax
 done
 
-	
-	altogether=""
+# Generation of 5TT image based on acpc registerred image
+5ttgen fsl anatomy/$subj\_t1_acpc.nii.gz $subj\_5tt.nii.gz
 
-	for z in lw_results*; do
-		altogether+="${z} "
-	done
+# Generate tractogram
 
-	tckedit $altogether lw_et.tck -force
+lmax="8 10 12"
+FAs="0.05"
+Curv="30 45 60"
+
+for i in $lmax; do
+  for j in $FAs; do
+    for k in $Curv; do
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_r_r_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_right.mif -include $subj\_end_right.mif -stop -step 0.2 -rk4; 
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_r_l_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_right.mif -include $subj\_end_left.mif -stop -step 0.2 -rk4; 
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_l_r_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_left.mif -include $subj\_end_right.mif -stop -step 0.2 -rk4; 
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_l_l_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_left.mif -include $subj\_end_left.mif -stop -step 0.2 -rk4; 
+      echo " "
+    done
+  done
+done
+
+altogether=""
 
-	# SIFT'em now to 9.6 mln
-	#tcksift ET_candidate.tck ../$i\_FOD.nii ET_candidate_sifted.tck -term_number 1000 -csv sifting_results.csv -force -info
+for z in *.tck; do
+  altogether+="${z} "
+done
 
-	# SIFT2 the results (maybe)
+tckedit $altogether $subj\_et.tck -force
 
-	#tcksift2 ET_candidate_sifted.tck ../$i\_FOD.nii ET_candidate_sifted_weights -force
 
-	# Clear the folder
-	#rm results*
-	#rm ET_candidate.tck
-}
+source 03_life.m $subj
 
-for r in $subjects; do 
-  analizuj "$r"
-  done
+#for r in $subjects; do 
+#  analizuj "$r"
+#  done
 	
+matlab -nodisplay -r 03_life.m
 
 
diff --git a/03_life.m b/03_life.m
index b11827d..b18b278 100644
--- a/03_life.m
+++ b/03_life.m
@@ -54,5 +54,7 @@
 set(gcf,'Color',[1 1 1])
 drawnow
 
+quit
+
 % save figure to disk
 print(fig_h,'my_figure','-dpng','-r600');%'-dpsc2')

From 4b911ae29df9e1d471118a1544ea6b5142d56f79 Mon Sep 17 00:00:00 2001
From: franco <frakkopesto@gmail.com>
Date: Tue, 14 Mar 2017 16:43:07 +0100
Subject: [PATCH 5/7] Script for checking preprocessing step

---
 000_view_preprocessing_results | 67 ++++++++++++++++++++++++++++++++++
 00_fsl_preprocess.sh           |  2 +-
 2 files changed, 68 insertions(+), 1 deletion(-)
 create mode 100644 000_view_preprocessing_results

diff --git a/000_view_preprocessing_results b/000_view_preprocessing_results
new file mode 100644
index 0000000..03c79d5
--- /dev/null
+++ b/000_view_preprocessing_results
@@ -0,0 +1,67 @@
+Check_preprocessing () {
+
+subj=$1
+
+low_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/$subj
+high_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+
+# View denoising maps. The less anatomical structures are visible the better
+mrview $low_res/Temporal/Distortions/$subj\_series*
+
+# Compare DWI before and after denoising for each encoding direction
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*AP_denoised.mif
+mrview $low_res/Temporal/*PA.mif $low_res/Temporal/*PA_denoised.mif
+
+# Compare mrtrix gradient for corrected DWI with original gradient table
+mrinfo $low_res/Temporal/$subj\_*AP_denoised.mif -export_grad_fsl $low_res/Temporal/bvecs $low_res/Temporal/bvals
+gedit $low_res/Temporal/bvecs &
+gedit $low_res/Temporal/Distortions/$subj\_gradients &
+gedit /home/auguser2016/dMRI_DATA/RAW_DATA/$subj*/s*/*ep2d*/*.bvec
+rm $low_res/Temporal/bvecs $low_res/Temporal/bvals
+
+# Compare DWI before and after dwipreproc
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*PA.mif $low_res/Temporal/$subj\_denoised_preproc.mif
+
+# View mask used for bias field correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif -overlay.load  $low_res/$subj\_clean_150mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View bias field
+mrview $low_res/Temporal/Distortions/$subj\_bias_field.mif
+
+# View DWI before and after bias correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif $low_res/$subj\_clean_150mm.mif
+
+# View normal and upsampled images
+mrview $low_res/$subj\_clean_150mm.mif $high_res/$subj\_clean_075mm.mif
+
+# View upsampled mask
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load  $high_res/$subj\_clean_075mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View SFR estimation voxels
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load $high_res/Temporal/$subj\_clean_075mm_SFR_voxels.mif
+
+# View SFR
+shview $high_res/$subj\_clean_075mm_SFR.txt
+
+# View anatomical image overlaid on upsampled FOD
+mrview $high_res/$subj\_clean_075mm.mif $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# View results of bet2
+mrview $high_res/$subj\_anatomical.nii.gz -overlay.load $high_res/Temporal/$subj\_anatomical_brain.nii.gz -overlay.opacity 0.3
+
+# View segmentation
+mrview $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.load $high_res/$subj\_075mm_5tt.nii.gz -overlay.opacity 0.3
+
+# Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+mrview $high_res/$subj\_075mm_5tt.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+
+5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+
+while true; do
+  mrview $high_res/$subj\_5tt_for_act_modified.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+  5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+done
+
+}
+
+for i in /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/*; do Check_preprocessing ${i: -4}; done
diff --git a/00_fsl_preprocess.sh b/00_fsl_preprocess.sh
index b8558eb..2f689b4 100644
--- a/00_fsl_preprocess.sh
+++ b/00_fsl_preprocess.sh
@@ -49,7 +49,7 @@ Preparation () {
 	dwi2mask $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_mask.mif
 
 	# Estimating single fibre response (SFR) for default lmax
-	dwi2response tournier $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_SFR.txt -shell 1600 -lmax 8 -mask $data/$high_res/$a\_clean_075mm_mask.mif -voxels $data/$high_res/Temporal/$a_clean_075mm_SFR_voxels.mif
+	dwi2response tournier $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_SFR.txt -shell 1600 -lmax 8 -mask $data/$high_res/$a\_clean_075mm_mask.mif -voxels $data/$high_res/Temporal/$a\_clean_075mm_SFR_voxels.mif
 
 	# Estimating FOD for previously obtained SFR
 	dwiextract $data/$high_res/$a\_clean_075mm.mif - | dwi2fod msmt_csd - $data/$high_res/$a\_clean_075mm_SFR.txt $data/$high_res/$a\_clean_075mm_FOD.mif -mask $data/$high_res/$a\_clean_075mm_mask.mif

From dc2f00854e0edcc1783a72a557cc9964e4ce53d6 Mon Sep 17 00:00:00 2001
From: franco <frakkopesto@gmail.com>
Date: Fri, 26 May 2017 19:32:48 +0200
Subject: [PATCH 6/7] Newest update - requires cleaning and merging

---
 00_fsl_preprocess.sh~          | 117 +++++++++++++++
 00_preprocess.sh               | 118 +++++++++++++++
 00_preprocess.sh~              | 117 +++++++++++++++
 01_check_preprocessing.sh      |  81 +++++++++++
 01_check_preprocessing.sh~     |  81 +++++++++++
 01_preparation_for_acpc.sh~    |  22 +++
 02_ensemble_tracking.txt~      |  63 ++++++++
 02_preparation_for_acpc.sh     |  21 +++
 02_t1_and_dwi_to_acpc.m~       |  47 ++++++
 03_t1_and_dwi_to_acpc (copy).m |  54 +++++++
 03_t1_and_dwi_to_acpc.m        |  51 +++++++
 03_working_on_original_lw.m    |  49 +++++++
 04_check_and_segment_acpc.sh   |  37 +++++
 04_check_and_segment_acpc.sh~  |  37 +++++
 04_postprocess.sh              |  48 ++++++
 04_postprocess.sh~             |  48 ++++++
 04_psychophysics.sh~           |   0
 05_ensemble_tracking.txt       | 258 +++++++++++++++++++++++++++++++++
 05_ensemble_tracking.txt~      | 198 +++++++++++++++++++++++++
 06_life.m                      |  59 ++++++++
 06_life_no_ACPC.m              |  79 ++++++++++
 07_results_evaluation.txt      |  59 ++++++++
 07_results_evaluation.txt~     |  39 +++++
 08_psychophysics.sh            |  19 +++
 Copy_of_06_life_ACPC.m         |  79 ++++++++++
 25 files changed, 1781 insertions(+)
 create mode 100644 00_fsl_preprocess.sh~
 create mode 100644 00_preprocess.sh
 create mode 100644 00_preprocess.sh~
 create mode 100644 01_check_preprocessing.sh
 create mode 100644 01_check_preprocessing.sh~
 create mode 100644 01_preparation_for_acpc.sh~
 create mode 100644 02_ensemble_tracking.txt~
 create mode 100644 02_preparation_for_acpc.sh
 create mode 100644 02_t1_and_dwi_to_acpc.m~
 create mode 100644 03_t1_and_dwi_to_acpc (copy).m
 create mode 100644 03_t1_and_dwi_to_acpc.m
 create mode 100644 03_working_on_original_lw.m
 create mode 100644 04_check_and_segment_acpc.sh
 create mode 100644 04_check_and_segment_acpc.sh~
 create mode 100644 04_postprocess.sh
 create mode 100644 04_postprocess.sh~
 create mode 100644 04_psychophysics.sh~
 create mode 100644 05_ensemble_tracking.txt
 create mode 100644 05_ensemble_tracking.txt~
 create mode 100644 06_life.m
 create mode 100644 06_life_no_ACPC.m
 create mode 100644 07_results_evaluation.txt
 create mode 100644 07_results_evaluation.txt~
 create mode 100644 08_psychophysics.sh
 create mode 100644 Copy_of_06_life_ACPC.m

diff --git a/00_fsl_preprocess.sh~ b/00_fsl_preprocess.sh~
new file mode 100644
index 0000000..1196ef9
--- /dev/null
+++ b/00_fsl_preprocess.sh~
@@ -0,0 +1,117 @@
+# Initializing
+
+# Folder with raw and preprocessed data
+data=/home/auguser2016/dMRI_DATA
+
+Genral_preprocessing () {
+
+	# 2 resolutions (1.5 mm and 0.75mm), inside each folder all preprocessed data sets of corresponding resolution with masks, map of distortions etc.
+	a=${1::-6}
+	
+	low_res=PREPROCESSED_DATA/1.5mm_iso/$a
+	high_res=PREPROCESSED_DATA/0.75mm_iso/$a
+
+	mkdir $data/$low_res
+	mkdir $data/$low_res/Temporal
+	mkdir $data/$low_res/Temporal/Distortions
+
+	mkdir $data/$high_res
+	mkdir $data/$high_res/Temporal
+	
+	
+	cd $data/RAW_DATA/${1::-1}/s*/
+
+	# Raw data files - DWI and anatomy - unpacked with MRIcron (dcm2nii) as a 4D Nifti images. Raw data goes: RAW_DATA/data_set_name/study.../studies_X/ where important are those with ep2d
+	# Transforming Nifti into .mif files and denoising them. Denoising is the very first that should be done - it's results can be viewed.
+	
+	for b in *ep2d*; do
+		cd $b
+		mrconvert *a001.nii -stride -1,2,3,4 -fslgrad *.bvec *.bval $data/$low_res/Temporal/$a\_$b\.mif 
+		dwidenoise $data/$low_res/Temporal/$a\_$b.mif $data/$low_res/Temporal/$a\_$b\_denoised.mif -noise $data/$low_res/Temporal/Distortions/$a\_$b\_noise.mif -debug
+	  	cd ..
+	done
+
+	# Script from MRtrix interacting with fsl. Here version for correcting DWI with 2 phase encoding directions is used
+	dwipreproc AP  $data/$low_res/Temporal/*AP_denoised.mif -rpe_all $data/$low_res/Temporal/*PA_denoised.mif $data/$low_res/Temporal/$a\_denoised_preproc.mif -export_grad_mrtrix $data/$low_res/Temporal/Distortions/$a\_gradients 
+	
+	# Masking preprocessed data. Results should be checked
+	dwi2mask $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm_mask.mif
+
+	# Masked is used for bias field correction using ANTS software
+	dwibiascorrect -ants $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm.mif -mask $data/$low_res/$a\_clean_150mm_mask.mif -bias $data/$low_res/Temporal/Distortions/$a\_bias_field.mif
+ 
+	# Preprocessing of 1.5 mm iso data sets done. Moving to upsampled resolution
+	
+	# Upsampling by factor of 2 to 0.75mm. Justified step, in FBA even factor 3 can be recommended
+	mrresize $data/$low_res/$a\_clean_150mm.mif -scale 2.0 $data/$high_res/$a\_clean_075mm.mif
+	
+	# Calculating mask again
+	dwi2mask $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Estimating single fibre response (SFR) for default lmax
+	dwi2response tournier $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_SFR.txt -shell 1600 -lmax 8 -mask $data/$high_res/$a\_clean_075mm_mask.mif -voxels $data/$high_res/Temporal/$a\_clean_075mm_SFR_voxels.mif
+
+	# Estimating FOD for previously obtained SFR
+	dwiextract $data/$high_res/$a\_clean_075mm.mif - | dwi2fod msmt_csd - $data/$high_res/$a\_clean_075mm_SFR.txt $data/$high_res/$a\_clean_075mm_FOD.mif -mask $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Performing coregistration of anatomical image to DWI images and segmenting it. It's easier approach as gradient table is not rotated this way. However for cross-modal studies it would be better to register DWI to anatomy
+
+	cd *MPRAGE*iso
+	
+	# Converting DWI image from .mif to .nii.gz as FSL likes. This step should be checked as well.
+	mrconvert $data/$high_res/$a\_clean_075mm.mif $data/$high_res/Temporal/$a\_clean_075mm.nii.gz
+	
+	# Coping anatomical image to corresponding folder
+	cp o* $data/$high_res/$a\_anatomical.nii.gz
+
+	# Extracting clean brain from anatomical image. Check this step
+	bet2 $data/$high_res/$a\_anatomical.nii.gz $data/$high_res/Temporal/$a\_anatomical_brain.nii.gz -f 0.6  	
+	
+	# Corregister DWI to anatomy
+	epi_reg --epi=$data/$high_res/Temporal/$a\_clean_075mm.nii.gz --t1=$data/$high_res/$a\_anatomical.nii.gz --t1brain=$data/$high_res/Temporal/$a\_anatomical_brain.nii.gz --out=$data/$high_res/Temporal/$a\_nodif2mprage_2 --echospacing=0.00023 --pedir=-y
+
+	# Reverse corregistration matrix
+	convert_xfm -inverse $data/$high_res/Temporal/$a\_nodif2mprage_2.mat -omat $data/$high_res/Temporal/$a\_mprage2nodif_2.mat
+
+	# Apply reverted matrix to corregister anatomy to DWI
+	flirt -in $data/$high_res/$a\_anatomical.nii.gz -ref $data/$high_res/Temporal/$a\_clean_075mm.nii.gz -out $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2 -applyxfm -init $data/$high_res/Temporal/$a\_mprage2nodif_2.mat -interp sinc -sincwidth 7 -sincwindow hanning
+
+	# Perform segmentation into WM, GM, subcortical GM, CSF and possible pathological tissue using FIRST from FSL
+	5ttgen fsl $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2.nii.gz $data/$high_res/$a\_075mm_5tt.nii.gz
+
+}
+
+cd $data/RAW_DATA
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+#list=(fe21_1325/)
+
+# This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
+
+for i in ${list[@]:0:3}; do Preparation $i & done
+wait
+for i in ${list[@]:3:6}; do Preparation $i & done
+wait
+for i in ${list[@]:6:9}; do Preparation $i & done
+wait
+for i in ${list[@]:9:12}; do Preparation $i & done
+wait
+for i in ${list[@]:12:15}; do Preparation $i & done
+wait
+for i in ${list[@]:15:18}; do Preparation $i & done
+wait
+for i in ${list[@]:18:21}; do Preparation $i & done
+wait
+for i in ${list[@]:21:24}; do Preparation $i & done
+wait
+for i in ${list[@]:24:27}; do Preparation $i & done
+wait
+for i in ${list[@]:27:30}; do Preparation $i & done
+wait
+for i in ${list[@]:30:33}; do Preparation $i & done
+wait
+
+# Returning to original folder
+cd /home/auguser2016/Scripts/
+
diff --git a/00_preprocess.sh b/00_preprocess.sh
new file mode 100644
index 0000000..67b2603
--- /dev/null
+++ b/00_preprocess.sh
@@ -0,0 +1,118 @@
+# Initializing
+
+# Folder with raw and preprocessed data
+data=/home/auguser2016/dMRI_DATA
+
+General_preprocessing () {
+
+	# 2 resolutions (1.5 mm and 0.75mm), inside each folder all preprocessed data sets of corresponding resolution with masks, map of distortions etc.
+	a=${1::-6}
+	
+	low_res=PREPROCESSED_DATA/1.5mm_iso/$a
+	high_res=PREPROCESSED_DATA/0.75mm_iso/$a
+
+	mkdir $data/$low_res
+	mkdir $data/$low_res/Temporal
+	mkdir $data/$low_res/Temporal/Distortions
+
+	mkdir $data/$high_res
+	mkdir $data/$high_res/Temporal
+	
+	
+	cd $data/RAW_DATA/${1::-1}/s*/
+
+	# Raw data files - DWI and anatomy - unpacked with MRIcron (dcm2nii) as a 4D Nifti images. Raw data goes: RAW_DATA/data_set_name/study.../studies_X/ where important are those with ep2d
+	# Transforming Nifti into .mif files and denoising them. Denoising is the very first that should be done - it's results can be viewed.
+	
+	for b in *ep2d*; do
+		cd $b
+		mrconvert *a001.nii -stride -1,2,3,4 -fslgrad *.bvec *.bval $data/$low_res/Temporal/$a\_$b\.mif 
+		dwidenoise $data/$low_res/Temporal/$a\_$b.mif $data/$low_res/Temporal/$a\_$b\_denoised.mif -noise $data/$low_res/Temporal/Distortions/$a\_$b\_noise.mif -debug
+	  	cd ..
+	done
+
+	# Script from MRtrix interacting with fsl. Here version for correcting DWI with 2 phase encoding directions is used
+	dwipreproc AP  $data/$low_res/Temporal/*AP_denoised.mif -rpe_all $data/$low_res/Temporal/*PA_denoised.mif $data/$low_res/Temporal/$a\_denoised_preproc.mif -export_grad_mrtrix $data/$low_res/Temporal/Distortions/$a\_gradients 
+	
+	# Masking preprocessed data. Results should be checked
+	dwi2mask $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm_mask.mif
+
+	# Masked is used for bias field correction using ANTS software
+	dwibiascorrect -ants $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm.mif -mask $data/$low_res/$a\_clean_150mm_mask.mif -bias $data/$low_res/Temporal/Distortions/$a\_bias_field.mif
+ 
+	# Preprocessing of 1.5 mm iso data sets done. Moving to upsampled resolution
+	
+	# Upsampling by factor of 2 to 0.75mm. Justified step, in FBA even factor 3 can be recommended
+	mrresize $data/$low_res/$a\_clean_150mm.mif -scale 2.0 $data/$high_res/$a\_clean_075mm.mif
+	
+	# Calculating mask again
+	dwi2mask $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Estimating single fibre response (SFR) for default lmax
+	dwi2response tournier $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_SFR.txt -shell 1600 -lmax 8 -mask $data/$high_res/$a\_clean_075mm_mask.mif -voxels $data/$high_res/Temporal/$a\_clean_075mm_SFR_voxels.mif
+
+	# Estimating FOD for previously obtained SFR
+	dwiextract $data/$high_res/$a\_clean_075mm.mif - | dwi2fod msmt_csd - $data/$high_res/$a\_clean_075mm_SFR.txt $data/$high_res/$a\_clean_075mm_FOD.mif -mask $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Performing coregistration of anatomical image to DWI images and segmenting it. It's easier approach as gradient table is not rotated this way. However for cross-modal studies it would be better to register DWI to anatomy
+
+	cd *MPRAGE*iso
+	
+	# Converting DWI image from .mif to .nii.gz as FSL likes. This step should be checked as well.
+	mrconvert $data/$high_res/$a\_clean_075mm.mif $data/$high_res/Temporal/$a\_clean_075mm.nii.gz
+	
+	# Coping anatomical image to corresponding folder
+	cp o* $data/$high_res/$a\_anatomical.nii.gz
+
+	# Extracting clean brain from anatomical image. Check this step
+	bet2 $data/$high_res/$a\_anatomical.nii.gz $data/$high_res/Temporal/$a\_anatomical_brain.nii.gz -f 0.6  	
+	
+	# Corregister DWI to anatomy
+	epi_reg --epi=$data/$high_res/Temporal/$a\_clean_075mm.nii.gz --t1=$data/$high_res/$a\_anatomical.nii.gz --t1brain=$data/$high_res/Temporal/$a\_anatomical_brain.nii.gz --out=$data/$high_res/Temporal/$a\_nodif2mprage_2 --echospacing=0.00023 --pedir=-y
+
+	# Reverse corregistration matrix
+	convert_xfm -inverse $data/$high_res/Temporal/$a\_nodif2mprage_2.mat -omat $data/$high_res/Temporal/$a\_mprage2nodif_2.mat
+
+	# Apply reverted matrix to corregister anatomy to DWI
+	flirt -in $data/$high_res/$a\_anatomical.nii.gz -ref $data/$high_res/Temporal/$a\_clean_075mm.nii.gz -out $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2 -applyxfm -init $data/$high_res/Temporal/$a\_mprage2nodif_2.mat -interp sinc -sincwidth 7 -sincwindow hanning
+
+	# Perform segmentation into WM, GM, subcortical GM, CSF and possible pathological tissue using FIRST from FSL
+	5ttgen fsl $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2.nii.gz $data/$high_res/$a\_075mm_5tt.nii.gz
+
+}
+
+cd $data/RAW_DATA
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+
+list=(uh47_1309/)
+
+# This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
+
+for i in ${list[@]:0:3}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:3:6}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:6:9}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:9:12}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:12:15}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:15:18}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:18:21}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:21:24}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:24:27}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:27:30}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:30:33}; do General_preprocessing $i & done
+wait
+
+# Returning to original folder
+cd /home/auguser2016/Scripts/
+
diff --git a/00_preprocess.sh~ b/00_preprocess.sh~
new file mode 100644
index 0000000..3985a09
--- /dev/null
+++ b/00_preprocess.sh~
@@ -0,0 +1,117 @@
+# Initializing
+
+# Folder with raw and preprocessed data
+data=/home/auguser2016/dMRI_DATA
+
+General_preprocessing () {
+
+	# 2 resolutions (1.5 mm and 0.75mm), inside each folder all preprocessed data sets of corresponding resolution with masks, map of distortions etc.
+	a=${1::-6}
+	
+	low_res=PREPROCESSED_DATA/1.5mm_iso/$a
+	high_res=PREPROCESSED_DATA/0.75mm_iso/$a
+
+	mkdir $data/$low_res
+	mkdir $data/$low_res/Temporal
+	mkdir $data/$low_res/Temporal/Distortions
+
+	mkdir $data/$high_res
+	mkdir $data/$high_res/Temporal
+	
+	
+	cd $data/RAW_DATA/${1::-1}/s*/
+
+	# Raw data files - DWI and anatomy - unpacked with MRIcron (dcm2nii) as a 4D Nifti images. Raw data goes: RAW_DATA/data_set_name/study.../studies_X/ where important are those with ep2d
+	# Transforming Nifti into .mif files and denoising them. Denoising is the very first that should be done - it's results can be viewed.
+	
+	for b in *ep2d*; do
+		cd $b
+		mrconvert *a001.nii -stride -1,2,3,4 -fslgrad *.bvec *.bval $data/$low_res/Temporal/$a\_$b\.mif 
+		dwidenoise $data/$low_res/Temporal/$a\_$b.mif $data/$low_res/Temporal/$a\_$b\_denoised.mif -noise $data/$low_res/Temporal/Distortions/$a\_$b\_noise.mif -debug
+	  	cd ..
+	done
+
+	# Script from MRtrix interacting with fsl. Here version for correcting DWI with 2 phase encoding directions is used
+	dwipreproc AP  $data/$low_res/Temporal/*AP_denoised.mif -rpe_all $data/$low_res/Temporal/*PA_denoised.mif $data/$low_res/Temporal/$a\_denoised_preproc.mif -export_grad_mrtrix $data/$low_res/Temporal/Distortions/$a\_gradients 
+	
+	# Masking preprocessed data. Results should be checked
+	dwi2mask $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm_mask.mif
+
+	# Masked is used for bias field correction using ANTS software
+	dwibiascorrect -ants $data/$low_res/Temporal/$a\_denoised_preproc.mif $data/$low_res/$a\_clean_150mm.mif -mask $data/$low_res/$a\_clean_150mm_mask.mif -bias $data/$low_res/Temporal/Distortions/$a\_bias_field.mif
+ 
+	# Preprocessing of 1.5 mm iso data sets done. Moving to upsampled resolution
+	
+	# Upsampling by factor of 2 to 0.75mm. Justified step, in FBA even factor 3 can be recommended
+	mrresize $data/$low_res/$a\_clean_150mm.mif -scale 2.0 $data/$high_res/$a\_clean_075mm.mif
+	
+	# Calculating mask again
+	dwi2mask $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Estimating single fibre response (SFR) for default lmax
+	dwi2response tournier $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm_SFR.txt -shell 1600 -lmax 8 -mask $data/$high_res/$a\_clean_075mm_mask.mif -voxels $data/$high_res/Temporal/$a\_clean_075mm_SFR_voxels.mif
+
+	# Estimating FOD for previously obtained SFR
+	dwiextract $data/$high_res/$a\_clean_075mm.mif - | dwi2fod msmt_csd - $data/$high_res/$a\_clean_075mm_SFR.txt $data/$high_res/$a\_clean_075mm_FOD.mif -mask $data/$high_res/$a\_clean_075mm_mask.mif
+
+	# Performing coregistration of anatomical image to DWI images and segmenting it. It's easier approach as gradient table is not rotated this way. However for cross-modal studies it would be better to register DWI to anatomy
+
+	cd *MPRAGE*iso
+	
+	# Converting DWI image from .mif to .nii.gz as FSL likes. This step should be checked as well.
+	mrconvert $data/$high_res/$a\_clean_075mm.mif $data/$high_res/Temporal/$a\_clean_075mm.nii.gz
+	
+	# Coping anatomical image to corresponding folder
+	cp o* $data/$high_res/$a\_anatomical.nii.gz
+
+	# Extracting clean brain from anatomical image. Check this step
+	bet2 $data/$high_res/$a\_anatomical.nii.gz $data/$high_res/Temporal/$a\_anatomical_brain.nii.gz -f 0.6  	
+	
+	# Corregister DWI to anatomy
+	epi_reg --epi=$data/$high_res/Temporal/$a\_clean_075mm.nii.gz --t1=$data/$high_res/$a\_anatomical.nii.gz --t1brain=$data/$high_res/Temporal/$a\_anatomical_brain.nii.gz --out=$data/$high_res/Temporal/$a\_nodif2mprage_2 --echospacing=0.00023 --pedir=-y
+
+	# Reverse corregistration matrix
+	convert_xfm -inverse $data/$high_res/Temporal/$a\_nodif2mprage_2.mat -omat $data/$high_res/Temporal/$a\_mprage2nodif_2.mat
+
+	# Apply reverted matrix to corregister anatomy to DWI
+	flirt -in $data/$high_res/$a\_anatomical.nii.gz -ref $data/$high_res/Temporal/$a\_clean_075mm.nii.gz -out $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2 -applyxfm -init $data/$high_res/Temporal/$a\_mprage2nodif_2.mat -interp sinc -sincwidth 7 -sincwindow hanning
+
+	# Perform segmentation into WM, GM, subcortical GM, CSF and possible pathological tissue using FIRST from FSL
+	5ttgen fsl $data/$high_res/$a\_075mm_anatomical_coreg2nodif_undist_2.nii.gz $data/$high_res/$a\_075mm_5tt.nii.gz
+
+}
+
+cd $data/RAW_DATA
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+
+
+# This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
+
+for i in ${list[@]:0:3}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:3:6}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:6:9}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:9:12}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:12:15}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:15:18}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:18:21}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:21:24}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:24:27}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:27:30}; do General_preprocessing $i & done
+wait
+for i in ${list[@]:30:33}; do General_preprocessing $i & done
+wait
+
+# Returning to original folder
+cd /home/auguser2016/Scripts/
+
diff --git a/01_check_preprocessing.sh b/01_check_preprocessing.sh
new file mode 100644
index 0000000..8b717c0
--- /dev/null
+++ b/01_check_preprocessing.sh
@@ -0,0 +1,81 @@
+Check_preprocessing () {
+
+subj=$1
+
+low_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/$subj
+high_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+
+# View denoising maps. The less anatomical structures are visible the better
+mrview $low_res/Temporal/Distortions/$subj\_series*
+
+# Compare DWI before and after denoising for each encoding direction
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*AP_denoised.mif
+mrview $low_res/Temporal/*PA.mif $low_res/Temporal/*PA_denoised.mif
+
+# Compare mrtrix gradient for corrected DWI with original gradient table
+mrinfo $low_res/Temporal/$subj\_*AP_denoised.mif -export_grad_fsl $low_res/Temporal/bvecs $low_res/Temporal/bvals
+gedit $low_res/Temporal/bvecs &
+gedit $low_res/Temporal/Distortions/$subj\_gradients &
+gedit /home/auguser2016/dMRI_DATA/RAW_DATA/$subj*/s*/*ep2d*/*.bvec
+rm $low_res/Temporal/bvecs $low_res/Temporal/bvals
+
+# Compare DWI before and after dwipreproc
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*PA.mif $low_res/Temporal/$subj\_denoised_preproc.mif
+
+# View mask used for bias field correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif -overlay.load  $low_res/$subj\_clean_150mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View bias field
+mrview $low_res/Temporal/Distortions/$subj\_bias_field.mif
+
+# View DWI before and after bias correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif $low_res/$subj\_clean_150mm.mif
+
+# View normal and upsampled images
+mrview $low_res/$subj\_clean_150mm.mif $high_res/$subj\_clean_075mm.mif
+
+# View upsampled mask
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load  $high_res/$subj\_clean_075mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View SFR estimation voxels
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load $high_res/Temporal/$subj\_clean_075mm_SFR_voxels.mif
+
+# View SFR
+shview $high_res/$subj\_clean_075mm_SFR.txt
+
+# View anatomical image overlaid on DWI
+mrview $high_res/$subj\_clean_075mm_FOD.mif $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# View results of bet2
+mrview $high_res/$subj\_anatomical.nii.gz -overlay.load $high_res/Temporal/$subj\_anatomical_brain.nii.gz -overlay.opacity 0.3
+
+# View segmentation
+mrview $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.load $high_res/$subj\_075mm_5tt.nii.gz -overlay.opacity 0.3
+
+# Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+mrview $high_res/$subj\_075mm_5tt.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+
+5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+
+while true; do
+  mrview $high_res/$subj\_5tt_for_act_modified.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+  5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+done
+
+#data=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+
+### Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+#mrview $data/$subj\_075mm_5tt.nii.gz -colourmap 3 -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $data/$subj\_5tt_patch.mif
+
+#5ttedit $data/$subj\_075mm_5tt.nii.gz -wm $data/$subj\_5tt_patch.mif $data/$subj\_075mm_5tt_modify.nii.gz -force
+
+#while true; do
+#  mrview $data/$subj\_075mm_5tt_modify.nii.gz -colourmap 3 -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $data/$subj\_5tt_patch.mif
+#  5ttedit $data/$subj\_075mm_5tt.nii.gz -wm $data/$subj\_5tt_patch.mif $data/$subj\_075mm_5tt_modify.nii.gz -force
+#done
+
+}
+
+#for i in /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/*; do Check_preprocessing ${i: -4}; done
+
+Check_preprocessing $1
diff --git a/01_check_preprocessing.sh~ b/01_check_preprocessing.sh~
new file mode 100644
index 0000000..8b717c0
--- /dev/null
+++ b/01_check_preprocessing.sh~
@@ -0,0 +1,81 @@
+Check_preprocessing () {
+
+subj=$1
+
+low_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/$subj
+high_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+
+# View denoising maps. The less anatomical structures are visible the better
+mrview $low_res/Temporal/Distortions/$subj\_series*
+
+# Compare DWI before and after denoising for each encoding direction
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*AP_denoised.mif
+mrview $low_res/Temporal/*PA.mif $low_res/Temporal/*PA_denoised.mif
+
+# Compare mrtrix gradient for corrected DWI with original gradient table
+mrinfo $low_res/Temporal/$subj\_*AP_denoised.mif -export_grad_fsl $low_res/Temporal/bvecs $low_res/Temporal/bvals
+gedit $low_res/Temporal/bvecs &
+gedit $low_res/Temporal/Distortions/$subj\_gradients &
+gedit /home/auguser2016/dMRI_DATA/RAW_DATA/$subj*/s*/*ep2d*/*.bvec
+rm $low_res/Temporal/bvecs $low_res/Temporal/bvals
+
+# Compare DWI before and after dwipreproc
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*PA.mif $low_res/Temporal/$subj\_denoised_preproc.mif
+
+# View mask used for bias field correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif -overlay.load  $low_res/$subj\_clean_150mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View bias field
+mrview $low_res/Temporal/Distortions/$subj\_bias_field.mif
+
+# View DWI before and after bias correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif $low_res/$subj\_clean_150mm.mif
+
+# View normal and upsampled images
+mrview $low_res/$subj\_clean_150mm.mif $high_res/$subj\_clean_075mm.mif
+
+# View upsampled mask
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load  $high_res/$subj\_clean_075mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View SFR estimation voxels
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load $high_res/Temporal/$subj\_clean_075mm_SFR_voxels.mif
+
+# View SFR
+shview $high_res/$subj\_clean_075mm_SFR.txt
+
+# View anatomical image overlaid on DWI
+mrview $high_res/$subj\_clean_075mm_FOD.mif $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# View results of bet2
+mrview $high_res/$subj\_anatomical.nii.gz -overlay.load $high_res/Temporal/$subj\_anatomical_brain.nii.gz -overlay.opacity 0.3
+
+# View segmentation
+mrview $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.load $high_res/$subj\_075mm_5tt.nii.gz -overlay.opacity 0.3
+
+# Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+mrview $high_res/$subj\_075mm_5tt.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+
+5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+
+while true; do
+  mrview $high_res/$subj\_5tt_for_act_modified.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+  5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+done
+
+#data=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+
+### Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+#mrview $data/$subj\_075mm_5tt.nii.gz -colourmap 3 -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $data/$subj\_5tt_patch.mif
+
+#5ttedit $data/$subj\_075mm_5tt.nii.gz -wm $data/$subj\_5tt_patch.mif $data/$subj\_075mm_5tt_modify.nii.gz -force
+
+#while true; do
+#  mrview $data/$subj\_075mm_5tt_modify.nii.gz -colourmap 3 -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $data/$subj\_5tt_patch.mif
+#  5ttedit $data/$subj\_075mm_5tt.nii.gz -wm $data/$subj\_5tt_patch.mif $data/$subj\_075mm_5tt_modify.nii.gz -force
+#done
+
+}
+
+#for i in /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/*; do Check_preprocessing ${i: -4}; done
+
+Check_preprocessing $1
diff --git a/01_preparation_for_acpc.sh~ b/01_preparation_for_acpc.sh~
new file mode 100644
index 0000000..dba2704
--- /dev/null
+++ b/01_preparation_for_acpc.sh~
@@ -0,0 +1,22 @@
+ACPC_preparation () {
+
+	# Registration to ACPC space requires preprocessed DWI image in .nii (or .nii.gz) format with corresponding bvecs and bvals. T1 image in ACPC space will be prepared separately
+
+	# Defining data set and its' path
+	a=${1::-6}
+	data=/home/auguser2016/dMRI_DATA
+	high_res=PREPROCESSED_DATA/0.75mm_iso/$a
+
+	# Obtain bvecs and bvals
+	mrinfo $data/$high_res/$a\_clean_075mm.mif -export_grad_fsl $data/$high_res/$a\_bvecs.bvecs $data/$high_res/$a\_bvals.bvals
+
+	# Transform DW in .mif into .nii.gz
+	mrconvert $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm.nii.gz
+}
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+list=(fe21_1325/)
+
+# As during processing of each data set full resources are used, lining them up is an effective approach
+for i in ${list[@]}; do ACPC_preparation $i; done
diff --git a/02_ensemble_tracking.txt~ b/02_ensemble_tracking.txt~
new file mode 100644
index 0000000..c5223eb
--- /dev/null
+++ b/02_ensemble_tracking.txt~
@@ -0,0 +1,63 @@
+# 1 Argument: ID of participant
+
+# Requirements:
+# Data preprocessed
+# DWI corregisterd to anatomy
+# Masks estimated
+# ROIs drawn
+
+subj=$1
+analysis_folder=/media/auguser2016/Volume/Quantifying_Chiasm
+
+mkdir $analysis_folder/$subj
+
+output=$analysis_folder/$subj
+
+# SFR Estimation
+lmax=6 'This should be as low as possible, optimal for most participants value #SFR for lower lmax, keep it and use higher 8,10,12 for fod estimation OR Get SFR with optimal lmax for most participants and use given lmax for all participants. Lower lmax preffered'
+dwi2response tournier $subj\_complete.mif -shell 1600 -lmax $lmax -mask $subj\_mask_upsampled.nii.gz $output/$subj\_sfr.txt 
+
+# Estimation of Fiber Orientation Distribution function
+for lmax in "8 10 12"; do  
+  dwiextract $subj\_complete.mif - | dwi2fod msmt_csd - $output/$subj\_sfr.txt $output/$subj\_fod_lmax_$lmax\.nii.gz -mask $subj\_mask_upsampled.nii.gz -lmax $lmax
+done
+
+# Generation of 5TT image based on acpc registerred image
+5ttgen fsl anatomy/$subj\_t1_acpc.nii.gz $subj\_5tt.nii.gz
+
+# Generate tractogram
+
+lmax="8 10 12"
+FAs="0.05"
+Curv="30 45 60"
+
+for i in $lmax; do
+  for j in $FAs; do
+    for k in $Curv; do
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_r_r_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_right.mif -include $subj\_end_right.mif -stop -step 0.2 -rk4; 
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_r_l_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_right.mif -include $subj\_end_left.mif -stop -step 0.2 -rk4; 
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_l_r_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_left.mif -include $subj\_end_right.mif -stop -step 0.2 -rk4; 
+      tckgen $subj\_fod_lmax_$lmax\.nii.gz lw_results_l_l_$i\_$j\_$k.tck -number 300 -cutoff $j -angle $k -act lw_5tt.nii.gz -unidirectional -seed_image $subj\_start_left.mif -include $subj\_end_left.mif -stop -step 0.2 -rk4; 
+      echo " "
+    done
+  done
+done
+
+altogether=""
+
+for z in *.tck; do
+  altogether+="${z} "
+done
+
+tckedit $altogether $subj\_et.tck -force
+
+
+source 03_life.m $subj
+
+#for r in $subjects; do 
+#  analizuj "$r"
+#  done
+	
+matlab -nodisplay -r 03_life.m
+
+
diff --git a/02_preparation_for_acpc.sh b/02_preparation_for_acpc.sh
new file mode 100644
index 0000000..ca1d232
--- /dev/null
+++ b/02_preparation_for_acpc.sh
@@ -0,0 +1,21 @@
+ACPC_preparation () {
+
+	# Registration to ACPC space requires preprocessed DWI image in .nii (or .nii.gz) format with corresponding bvecs and bvals. T1 image in ACPC space will be prepared separately
+
+	# Defining data set and its' path
+	a=${1::-6}
+	data=/home/auguser2016/dMRI_DATA
+	high_res=PREPROCESSED_DATA/0.75mm_iso/$a
+
+	# Obtain bvecs and bvals
+	mrinfo $data/$high_res/$a\_clean_075mm.mif -export_grad_fsl $data/$high_res/$a\_bvecs.bvecs $data/$high_res/$a\_bvals.bvals
+
+	# Transform DW in .mif into .nii.gz
+	mrconvert $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm.nii.gz
+}
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+
+# As during processing of each data set full resources are used, lining them up is an effective approach
+for i in ${list[@]}; do ACPC_preparation $i; done
diff --git a/02_t1_and_dwi_to_acpc.m~ b/02_t1_and_dwi_to_acpc.m~
new file mode 100644
index 0000000..401e4a3
--- /dev/null
+++ b/02_t1_and_dwi_to_acpc.m~
@@ -0,0 +1,47 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/francopestilli-life-aea5433'))
+
+% ACPC registration for T1 in each data set performed manually
+% Done manually
+
+% Perform Diffusion Imaging Processing for all data sets
+cd /home/auguser2016/Projects/Chiasm_RJP_FP/
+subjects=dir
+
+%for i=3:size(subjects,1)
+    
+    %id=subjects(i).name
+    id='ib57'
+    
+    % Prepare data in form acceptable by dtiInit
+    % ACPC registerred T1 image
+    anatomy=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP/',id,'/',id,'_t1_acpc.nii.gz')
+    % Diffusion Data (motion, eddy and geometrical distortions corrected)
+    dwi=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'_clean_075mm.nii.gz')
+    % bvecs and bvals obtained from corrected DW images
+    bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'.bvecs')
+    bvals=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'.bvals')
+    
+    % Set up dtiInit paramters specific for our study
+    dwParams = dtiInitParams;
+    dwParams.rotateBvecsWithRx = 1;
+    dwParams.rotateBvecsWithCanXform = 1;
+    dwParams.bvecsFile = fullfile(bvecs);
+    dwParams.bvalsFile = fullfile(bvals);
+    dwParams.eddyCorrect = -1;
+    dwParams.dwOutMm = [1.5 1.5 1.5];
+    dwParams.phaseEncodeDir = 2;
+    dwParams.outDir = fullfile(pwd,'dtiInitPreprocessed');
+
+    % Start Diffusion Imaging preprocessing.
+    [dt6FileName, outBaseDir] = dtiInit(dwi,...
+                                        anatomy, ...
+                                        dwParams); 
+%end
+
+
+
+
diff --git a/03_t1_and_dwi_to_acpc (copy).m b/03_t1_and_dwi_to_acpc (copy).m
new file mode 100644
index 0000000..1093782
--- /dev/null
+++ b/03_t1_and_dwi_to_acpc (copy).m	
@@ -0,0 +1,54 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% ACPC registration for T1 in each data set performed manually
+% Done manually
+
+% Perform Diffusion Imaging Processing for all data sets
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/
+subjects=dir
+
+%for i=22:size(subjects,1)
+    
+    %id=subjects(i).name
+    id='uf97'
+    % Prepare data in form acceptable by dtiInit
+    
+    % ACPC registerred T1 image
+    anatomy=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_t1_acpc.nii.gz')
+    
+    % Diffusion Data (motion, eddy and geometrical distortions corrected)
+    dwi=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_clean_150mm.nii.gz')
+    
+    % Bvecs and bvals obtained from corrected DW images
+    bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvecs.bvecs')
+    bvals=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvals.bvals')
+  
+    bvecs_rot = dlmread(bvecs);
+    bvecs_rot(2,:)=-bvecs_rot(2,:);
+    dlmwrite(strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvecs_rot.bvecs'), bvecs_rot)
+    
+    % Output directory
+    output=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'_0p5/')
+    
+    % Set up dtiInit paramters specific for our study
+    dwParams = dtiInitParams;
+    dwParams.rotateBvecsWithRx = 1;
+    dwParams.rotateBvecsWithCanXform = 0;
+    dwParams.bvecsFile = fullfile(bvecs);
+    dwParams.bvalsFile = fullfile(bvals);
+    dwParams.eddyCorrect = -1;
+    dwParams.dwOutMm = [0.75 0.75 0.75]; % change this to 1.5 and process 0.75 anyway
+    %dwParams.dwOutMm = [1.5 1.5 1.5];
+    dwParams.phaseEncodeDir = 2;
+    dwParams.outDir=output
+    %dwParams.outDir = fullfile(pwd,'dtiInitPreprocessed');
+
+    % Start Diffusion Imaging preprocessing.
+    [dt6FileName, outBaseDir] = dtiInit(dwi,...
+                                        anatomy, ...
+                                        dwParams); 
+%end
diff --git a/03_t1_and_dwi_to_acpc.m b/03_t1_and_dwi_to_acpc.m
new file mode 100644
index 0000000..b1db325
--- /dev/null
+++ b/03_t1_and_dwi_to_acpc.m
@@ -0,0 +1,51 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% ACPC registration for T1 in each data set performed manually
+% Done manually
+
+% Perform Diffusion Imaging Processing for all data sets
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/
+subjects=dir
+
+for i=5:size(subjects,1)
+    
+    id=subjects(i).name
+    %id='fe21'
+    % Prepare data in form acceptable by dtiInit
+    
+    % ACPC registerred T1 image
+    anatomy=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_t1_acpc.nii.gz')
+    
+    % Diffusion Data (motion, eddy and geometrical distortions corrected)
+    dwi=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'_clean_075mm.nii.gz')
+    %dwi=strcat('/media/auguser2016/Volume/Test/lw37.nii.gz')
+    
+    % Bvecs and bvals obtained from corrected DW images
+    bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'_bvecs.bvecs')
+    bvals=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'_bvals.bvals')
+  
+    % Output directory
+    output=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/')
+    
+    % Set up dtiInit paramters specific for our study
+    dwParams = dtiInitParams;
+    dwParams.rotateBvecsWithRx = 1;
+    dwParams.rotateBvecsWithCanXform = 0;
+    dwParams.bvecsFile = fullfile(bvecs);
+    dwParams.bvalsFile = fullfile(bvals);
+    dwParams.eddyCorrect = -1;
+    dwParams.dwOutMm = [0.75 0.75 0.75]; % change this to 1.5 and process 0.75 anyway
+    %dwParams.dwOutMm = [1.5 1.5 1.5];
+    dwParams.phaseEncodeDir = 2;
+    dwParams.outDir=output
+    %dwParams.outDir = fullfile(pwd,'dtiInitPreprocessed');
+
+    % Start Diffusion Imaging preprocessing.
+    [dt6FileName, outBaseDir] = dtiInit(dwi,...
+                                        anatomy, ...
+                                        dwParams); 
+end
diff --git a/03_working_on_original_lw.m b/03_working_on_original_lw.m
new file mode 100644
index 0000000..6ae4082
--- /dev/null
+++ b/03_working_on_original_lw.m
@@ -0,0 +1,49 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% ACPC registration for T1 in each data set performed manually
+% Done manually
+
+% Perform Diffusion Imaging Processing for all data sets
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/
+subjects=dir
+
+for i=5:size(subjects,1)
+    
+    id=subjects(i).name
+    % Prepare data in form acceptable by dtiInit
+    
+    % ACPC registerred T1 image
+    anatomy=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_t1_acpc.nii.gz')
+    
+    % Diffusion Data (motion, eddy and geometrical distortions corrected)
+    dwi=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_clean_150mm.nii.gz')
+    
+    % Bvecs and bvals obtained from corrected DW images
+    bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvecs.bvecs')
+    bvals=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvals.bvals')
+  
+    % Output directory
+    output=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/')
+    
+    % Set up dtiInit paramters specific for our study
+    dwParams = dtiInitParams;
+    dwParams.rotateBvecsWithRx = 1;
+    dwParams.rotateBvecsWithCanXform = 0;
+    dwParams.bvecsFile = fullfile(bvecs);
+    dwParams.bvalsFile = fullfile(bvals);
+    dwParams.eddyCorrect = -1;
+    dwParams.dwOutMm = [0.75 0.75 0.75]; % change this to 1.5 and process 0.75 anyway
+    %dwParams.dwOutMm = [1.5 1.5 1.5];
+    dwParams.phaseEncodeDir = 2;
+    dwParams.outDir=output
+    %dwParams.outDir = fullfile(pwd,'dtiInitPreprocessed');
+
+    % Start Diffusion Imaging preprocessing.
+    [dt6FileName, outBaseDir] = dtiInit(dwi,...
+                                        anatomy, ...
+                                        dwParams); 
+end
diff --git a/04_check_and_segment_acpc.sh b/04_check_and_segment_acpc.sh
new file mode 100644
index 0000000..c7e7aab
--- /dev/null
+++ b/04_check_and_segment_acpc.sh
@@ -0,0 +1,37 @@
+Check_acpc () {
+
+subj=$1
+
+analysis=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+
+# Compare coregisterred DW image with anatomy in acpc space
+#mrview $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_t1_acpc.nii.gz
+
+# Compare DW images before and after registration
+#mrview $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.nii.gz /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_clean_075mm.mif
+
+# Compare their bvecs
+#gedit $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.bvecs /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_bvecs.bvecs
+
+# Compare their bvals
+#gedit $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.bvals /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_bvals.bvals
+
+# for ACPC registration
+# Perform segmentation of T1 image in ACPC space into WM, GM, subGM, CSF and potential pathological tissue
+5ttgen fsl $analysis/$subj\_t1_acpc.nii.gz $analysis/$subj\_t1_acpc_5tt.nii.gz
+
+# Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+#mrview $analysis/$subj\_t1_acpc_5tt.nii.gz -colourmap 3 -overlay.load $analysis/$subj\_t1_acpc.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $analysis/$subj\_5tt_patch.mif
+
+#5ttedit $analysis/$subj\_t1_acpc_5tt.nii.gz -wm $analysis/$subj\_5tt_patch.mif $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -force
+
+#while true; do
+#  mrview $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -colourmap 3 -overlay.load $analysis/$subj\_t1_acpc.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $analysis/$subj\_5tt_patch.mif
+#  5ttedit $analysis/$subj\_t1_acpc_5tt.nii.gz -wm $analysis/$subj\_5tt_patch.mif $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -force
+#done
+
+}
+
+#for i in /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/*; do Check_acpc ${i: -4}; done
+
+Check_acpc $1
diff --git a/04_check_and_segment_acpc.sh~ b/04_check_and_segment_acpc.sh~
new file mode 100644
index 0000000..f80a62c
--- /dev/null
+++ b/04_check_and_segment_acpc.sh~
@@ -0,0 +1,37 @@
+Check_acpc () {
+
+subj=$1
+
+analysis=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+
+# Compare coregisterred DW image with anatomy in acpc space
+#mrview $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_t1_acpc.nii.gz
+
+# Compare DW images before and after registration
+#mrview $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.nii.gz /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_clean_075mm.mif
+
+# Compare their bvecs
+#gedit $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.bvecs /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_bvecs.bvecs
+
+# Compare their bvals
+#gedit $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.bvals /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_bvals.bvals
+
+# for ACPC registration
+# Perform segmentation of T1 image in ACPC space into WM, GM, subGM, CSF and potential pathological tissue
+5ttgen fsl $analysis/$subj\_t1_acpc.nii.gz $analysis/$subj\_t1_acpc_5tt.nii.gz
+
+# Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+#mrview $analysis/$subj\_t1_acpc_5tt.nii.gz -colourmap 3 -overlay.load $analysis/$subj\_t1_acpc.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $analysis/$subj\_5tt_patch.mif
+
+#5ttedit $analysis/$subj\_t1_acpc_5tt.nii.gz -wm $analysis/$subj\_5tt_patch.mif $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -force
+
+#while true; do
+#  mrview $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -colourmap 3 -overlay.load $analysis/$subj\_t1_acpc.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $analysis/$subj\_5tt_patch.mif
+#  5ttedit $analysis/$subj\_t1_acpc_5tt.nii.gz -wm $analysis/$subj\_5tt_patch.mif $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -force
+#done
+
+}
+
+#for i in /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/*; do Check_acpc ${i: -4}; done
+
+Check_acpc hw91
diff --git a/04_postprocess.sh b/04_postprocess.sh
new file mode 100644
index 0000000..57463de
--- /dev/null
+++ b/04_postprocess.sh
@@ -0,0 +1,48 @@
+General_postprocessing () {
+
+subj=${1::-6}
+
+analysis=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+
+dwi2mask $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_mask.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+
+# Estimating single fibre response (SFR) for lmax=6
+dwi2response tournier $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_SFR.txt -shell 1600 -lmax 6 -mask $analysis/$subj\_acpc_mask.nii.gz  -voxels $analysis/$subj\_acpc_SFR_voxels.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+
+# Estimation of Fiber Orientation Distribution function for 3 lmax
+for lmax in 8 10 12; do  
+  dwiextract $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals - | dwi2fod msmt_csd - $analysis/$subj\_acpc_SFR.txt -lmax $lmax $analysis/$subj\_acpc_FOD_lmax_$lmax.mif -mask $analysis/$subj\_acpc_mask.nii.gz 
+done
+}
+
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+
+list=(uf97_1072/) #ow93_0974/ )
+
+
+# This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
+
+for i in ${list[@]:0:3}; do General_postprocessing $i; done
+wait
+for i in ${list[@]:3:6}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:6:9}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:9:12}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:12:15}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:15:18}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:18:21}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:21:24}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:24:27}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:27:30}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:30:33}; do General_postprocessing $i & done
+wait
diff --git a/04_postprocess.sh~ b/04_postprocess.sh~
new file mode 100644
index 0000000..645b497
--- /dev/null
+++ b/04_postprocess.sh~
@@ -0,0 +1,48 @@
+General_postprocessing () {
+
+subj=${1::-6}
+
+analysis=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+
+dwi2mask $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_mask.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+
+# Estimating single fibre response (SFR) for lmax=6
+dwi2response tournier $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_SFR.txt -shell 1600 -lmax 6 -mask $analysis/$subj\_acpc_mask.nii.gz  -voxels $analysis/$subj\_acpc_SFR_voxels.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+
+# Estimation of Fiber Orientation Distribution function for 3 lmax
+for lmax in 8 10 12; do  
+  dwiextract $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals - | dwi2fod msmt_csd - $analysis/$subj\_acpc_SFR.txt -lmax $lmax $analysis/$subj\_acpc_FOD_lmax_$lmax.mif -mask $analysis/$subj\_acpc_mask.nii.gz 
+done
+}
+
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+
+list=(uh47_1309/) #uf97_1072/ ow93_0974/ )
+
+
+# This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
+
+for i in ${list[@]:0:3}; do General_postprocessing $i; done
+wait
+for i in ${list[@]:3:6}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:6:9}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:9:12}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:12:15}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:15:18}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:18:21}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:21:24}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:24:27}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:27:30}; do General_postprocessing $i & done
+wait
+for i in ${list[@]:30:33}; do General_postprocessing $i & done
+wait
diff --git a/04_psychophysics.sh~ b/04_psychophysics.sh~
new file mode 100644
index 0000000..e69de29
diff --git a/05_ensemble_tracking.txt b/05_ensemble_tracking.txt
new file mode 100644
index 0000000..754fb82
--- /dev/null
+++ b/05_ensemble_tracking.txt
@@ -0,0 +1,258 @@
+# 1 Argument: ID of participant
+
+# Requirements:
+# Data preprocessed
+# DWI corregisterd to anatomy
+# Done and corrected 5TT segmentation
+
+ROIs_tracking_anatomy () {
+
+subj=$1
+data=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+output=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $output
+mkdir $output/Tractography_dwi
+cd $output
+
+# Manually create 4 ROIs for given data set
+#mrview $data/$subj\_clean_075mm_FOD.mif -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# SFR Estimation
+lmax=6 #This should be as low as possible, optimal for most participants value #SFR for lower lmax, keep it and use higher 8,10,12 for fod estimation OR Get SFR with optimal lmax for most participants and use given lmax for all participants. Lower lmax preffered
+#dwi2response tournier $data/$subj\_clean_075mm.mif -shell 1600 -lmax $lmax -mask $data/$subj\_clean_075mm_mask.mif $output/$subj\_sfr.txt -voxels $data/Temporal/$subj\_SFR_voxels.mif
+
+# Estimation of Fiber Orientation Distribution function
+#for lmax in 8 10 12; do  
+#  dwiextract $data/$subj\_clean_075mm.mif - | dwi2fod msmt_csd - $output/$subj\_sfr.txt -lmax $lmax $output/$subj\_FOD_lmax_$lmax.mif -mask $data/$subj\_clean_075mm_mask.mif
+#done
+
+# Generation of 5TT image based on acpc registerred image
+#5ttgen fsl anatomy/$subj\_t1_acpc.nii.gz $subj\_5tt.nii.gz
+
+# Generate tractogram
+
+lmax="8 10 12"
+FAs="0.05"
+Curv="30 45 60"
+
+tt_image=$data/$subj\_5tt_for_act_modified.nii.gz
+
+for i in $lmax; do
+  for j in $FAs; do
+    for k in $Curv; do
+      echo $subj\_results_r_r_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_r_l_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_r_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_l_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      
+      #echo $subj\_results_r_r_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_r_l_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_r_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_l_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output//$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      
+      
+      echo $subj\_results_r_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_r_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_left.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_left.mif -include $output/$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      
+      echo $subj\_results_r_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_r_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_left.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_left.mif -include $output//$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      
+      echo " "
+    done
+  done
+done
+
+
+
+cd $output/Tractography
+
+tckedit *_??.tck $subj\_ACT.tck
+tckedit *r_r*_??.tck $subj\_r_r_ACT.tck
+tckedit *r_l*_??.tck $subj\_r_l_ACT.tck
+tckedit *l_r*_??.tck $subj\_l_r_ACT.tck
+tckedit *l_l*_??.tck $subj\_l_l_ACT.tck
+
+tckedit *_no_ACT.tck $subj\_no_ACT.tck
+tckedit *r_r*_no_ACT.tck $subj\_r_r_no_ACT.tck
+tckedit *r_l*_no_ACT.tck $subj\_r_l_no_ACT.tck
+tckedit *l_r*_no_ACT.tck $subj\_l_r_no_ACT.tck
+tckedit *l_l*_no_ACT.tck $subj\_l_l_no_ACT.tck
+
+}
+
+ROIs_tracking_dwi () {
+
+subj=$1
+data=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+output=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $output
+mkdir $output/Tractography_dwi
+cd $output
+
+# Manually create 4 ROIs for given data set
+#mrview $data/$subj\_clean_075mm_FOD.mif -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# SFR Estimation
+lmax=6 #This should be as low as possible, optimal for most participants value #SFR for lower lmax, keep it and use higher 8,10,12 for fod estimation OR Get SFR with optimal lmax for most participants and use given lmax for all participants. Lower lmax preffered
+#dwi2response tournier $data/$subj\_clean_075mm.mif -shell 1600 -lmax $lmax -mask $data/$subj\_clean_075mm_mask.mif $output/$subj\_sfr.txt -voxels $data/Temporal/$subj\_SFR_voxels.mif
+
+# Estimation of Fiber Orientation Distribution function
+#for lmax in 8 10 12; do  
+#  dwiextract $data/$subj\_clean_075mm.mif - | dwi2fod msmt_csd - $output/$subj\_sfr.txt -lmax $lmax $output/$subj\_FOD_lmax_$lmax.mif -mask $data/$subj\_clean_075mm_mask.mif
+#done
+
+# Generation of 5TT image based on acpc registerred image
+#5ttgen fsl anatomy/$subj\_t1_acpc.nii.gz $subj\_5tt.nii.gz
+
+# Generate tractogram
+
+lmax="8 10 12"
+FAs="0.05"
+Curv="30 45 60"
+
+tt_image=$data/$subj\_5tt_for_act_modified_dwi.nii.gz
+
+for i in $lmax; do
+  for j in $FAs; do
+    for k in $Curv; do
+      echo $subj\_results_r_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_r_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      
+      echo $subj\_results_r_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_r_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output//$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      
+      echo " "
+    done
+  done
+done
+
+
+
+cd $output/Tractography_dwi
+
+tckedit *_??.tck $subj\_ACT.tck
+tckedit *r_r*_??.tck $subj\_r_r_ACT.tck
+tckedit *r_l*_??.tck $subj\_r_l_ACT.tck
+tckedit *l_r*_??.tck $subj\_l_r_ACT.tck
+tckedit *l_l*_??.tck $subj\_l_l_ACT.tck
+
+tckedit *_no_ACT.tck $subj\_no_ACT.tck
+tckedit *r_r*_no_ACT.tck $subj\_r_r_no_ACT.tck
+tckedit *r_l*_no_ACT.tck $subj\_r_l_no_ACT.tck
+tckedit *l_r*_no_ACT.tck $subj\_l_r_no_ACT.tck
+tckedit *l_l*_no_ACT.tck $subj\_l_l_no_ACT.tck
+
+}
+
+
+ACPC_tracking () {
+
+subj=$1
+data=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+output=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+
+
+mkdir $output/Tractography
+cd $output
+
+# SFR Estimation
+#lmax=6 #This should be as low as possible, optimal for most participants value #SFR for lower lmax, keep it and use higher 8,10,12 for fod estimation OR Get SFR with optimal lmax for most participants and use given lmax for all participants. Lower lmax preffered
+#dwi2response tournier $data/$subj\_clean_075mm.mif -shell 1600 -lmax $lmax -mask $data/$subj\_clean_075mm_mask.mif $output/$subj\_sfr.txt -voxels $data/Temporal/$subj\_SFR_voxels.mif
+
+# Estimation of Fiber Orientation Distribution function
+#for lmax in 8 10 12; do  
+#  dwiextract $data/$subj\_clean_075mm.mif - | dwi2fod msmt_csd - $output/$subj\_sfr.txt -lmax $lmax $output/$subj\_FOD_lmax_$lmax.mif -mask $data/$subj\_clean_075mm_mask.mif
+#done
+
+# Generation of 5TT image based on acpc registerred image
+#5ttgen fsl anatomy/$subj\_t1_acpc.nii.gz $subj\_5tt.nii.gz
+
+# Generate tractogram
+
+lmax="8 10 12"
+FAs="0.05"
+Curv="30 45 60"
+
+tt_image=$data/$subj\_t1_acpc_5tt_corrected.nii.gz
+#tt_image=$data/$subj\_t1_acpc_5tt.nii.gz
+
+for i in $lmax; do
+  for j in $FAs; do
+    for k in $Curv; do
+      echo $subj\_results_r_r_$i\_$j\_$k
+      tckgen $output/$subj\_acpc_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/ROIs/$subj\_sr.mif -include $output/ROIs/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_r_l_$i\_$j\_$k
+      tckgen $output/$subj\_acpc_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/ROIs/$subj\_sr.mif -include $output/ROIs/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_r_$i\_$j\_$k
+      tckgen $output/$subj\_acpc_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/ROIs/$subj\_sl.mif -include $output/ROIs/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_l_$i\_$j\_$k
+      tckgen $output/$subj\_acpc_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/ROIs/$subj\_sl.mif -include $output/ROIs/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      
+      echo " "
+    done
+  done
+done
+
+
+
+cd $output/Tractography
+
+tckedit *_??.tck $subj\_ACT.tck
+tckedit *r_r*_??.tck $subj\_r_r_ACT.tck
+tckedit *r_l*_??.tck $subj\_r_l_ACT.tck
+tckedit *l_r*_??.tck $subj\_l_r_ACT.tck
+tckedit *l_l*_??.tck $subj\_l_l_ACT.tck
+
+}
+
+
+
+
+
+#for i in /home/auguser2016/Projects/Chiasm_RJP_FP/*; do ROIs_tracking ${i: -4}; done
+
+
+
+ACPC_tracking $1
+
+#source 03_life.m $subj
+
+#for r in $subjects; do 
+#  analizuj "$r"
+#  done
+	
+#matlab -nodisplay -r 03_life.m
+
+
diff --git a/05_ensemble_tracking.txt~ b/05_ensemble_tracking.txt~
new file mode 100644
index 0000000..26238c5
--- /dev/null
+++ b/05_ensemble_tracking.txt~
@@ -0,0 +1,198 @@
+# 1 Argument: ID of participant
+
+# Requirements:
+# Data preprocessed
+# DWI corregisterd to anatomy
+# Done and corrected 5TT segmentation
+
+ROIs_tracking_anatomy () {
+
+subj=$1
+data=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+output=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $output
+mkdir $output/Tractography_dwi
+cd $output
+
+# Manually create 4 ROIs for given data set
+#mrview $data/$subj\_clean_075mm_FOD.mif -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# SFR Estimation
+lmax=6 #This should be as low as possible, optimal for most participants value #SFR for lower lmax, keep it and use higher 8,10,12 for fod estimation OR Get SFR with optimal lmax for most participants and use given lmax for all participants. Lower lmax preffered
+#dwi2response tournier $data/$subj\_clean_075mm.mif -shell 1600 -lmax $lmax -mask $data/$subj\_clean_075mm_mask.mif $output/$subj\_sfr.txt -voxels $data/Temporal/$subj\_SFR_voxels.mif
+
+# Estimation of Fiber Orientation Distribution function
+#for lmax in 8 10 12; do  
+#  dwiextract $data/$subj\_clean_075mm.mif - | dwi2fod msmt_csd - $output/$subj\_sfr.txt -lmax $lmax $output/$subj\_FOD_lmax_$lmax.mif -mask $data/$subj\_clean_075mm_mask.mif
+#done
+
+# Generation of 5TT image based on acpc registerred image
+#5ttgen fsl anatomy/$subj\_t1_acpc.nii.gz $subj\_5tt.nii.gz
+
+# Generate tractogram
+
+lmax="8 10 12"
+FAs="0.05"
+Curv="30 45 60"
+
+tt_image=$data/$subj\_5tt_for_act_modified.nii.gz
+
+for i in $lmax; do
+  for j in $FAs; do
+    for k in $Curv; do
+      echo $subj\_results_r_r_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_r_l_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_r_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_l_$i\_$j\_$k
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      
+      #echo $subj\_results_r_r_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_r_l_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_r_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 100000; 
+      #echo $subj\_results_l_l_$i\_$j\_$k\_no_ACT
+      #tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output//$subj\_el.mif -stop -step 0.2 -maxnum 100000; 
+      
+      
+      echo $subj\_results_r_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_r_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_left.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $data/$subj\_5tt_for_act_modified.nii.gz -unidirectional -seed_image $output/$subj\_start_left.mif -include $output/$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      
+      echo $subj\_results_r_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_r_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_r_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_right.mif -include $output/$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_left.mif -include $output/$subj\_end_right.mif -stop -step 0.2 -maxnum 100000; 
+      echo $subj\_results_l_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography/$subj\_results_l_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff 0.10 -angle $k -unidirectional -seed_image $output/$subj\_start_left.mif -include $output//$subj\_end_left.mif -stop -step 0.2 -maxnum 100000; 
+      
+      echo " "
+    done
+  done
+done
+
+
+
+cd $output/Tractography
+
+tckedit *_??.tck $subj\_ACT.tck
+tckedit *r_r*_??.tck $subj\_r_r_ACT.tck
+tckedit *r_l*_??.tck $subj\_r_l_ACT.tck
+tckedit *l_r*_??.tck $subj\_l_r_ACT.tck
+tckedit *l_l*_??.tck $subj\_l_l_ACT.tck
+
+tckedit *_no_ACT.tck $subj\_no_ACT.tck
+tckedit *r_r*_no_ACT.tck $subj\_r_r_no_ACT.tck
+tckedit *r_l*_no_ACT.tck $subj\_r_l_no_ACT.tck
+tckedit *l_r*_no_ACT.tck $subj\_l_r_no_ACT.tck
+tckedit *l_l*_no_ACT.tck $subj\_l_l_no_ACT.tck
+
+}
+
+ROIs_tracking_dwi () {
+
+subj=$1
+data=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+output=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $output
+mkdir $output/Tractography_dwi
+cd $output
+
+# Manually create 4 ROIs for given data set
+#mrview $data/$subj\_clean_075mm_FOD.mif -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# SFR Estimation
+lmax=6 #This should be as low as possible, optimal for most participants value #SFR for lower lmax, keep it and use higher 8,10,12 for fod estimation OR Get SFR with optimal lmax for most participants and use given lmax for all participants. Lower lmax preffered
+#dwi2response tournier $data/$subj\_clean_075mm.mif -shell 1600 -lmax $lmax -mask $data/$subj\_clean_075mm_mask.mif $output/$subj\_sfr.txt -voxels $data/Temporal/$subj\_SFR_voxels.mif
+
+# Estimation of Fiber Orientation Distribution function
+#for lmax in 8 10 12; do  
+#  dwiextract $data/$subj\_clean_075mm.mif - | dwi2fod msmt_csd - $output/$subj\_sfr.txt -lmax $lmax $output/$subj\_FOD_lmax_$lmax.mif -mask $data/$subj\_clean_075mm_mask.mif
+#done
+
+# Generation of 5TT image based on acpc registerred image
+#5ttgen fsl anatomy/$subj\_t1_acpc.nii.gz $subj\_5tt.nii.gz
+
+# Generate tractogram
+
+lmax="8 10 12"
+FAs="0.05"
+Curv="30 45 60"
+
+tt_image=$data/$subj\_5tt_for_act_modified_dwi.nii.gz
+
+for i in $lmax; do
+  for j in $FAs; do
+    for k in $Curv; do
+      echo $subj\_results_r_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_r_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_r_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_r_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_l_$i\_$j\_$k
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_l_$i\_$j\_$k.tck -number 200 -cutoff $j -angle $k -act $tt_image -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      
+      echo $subj\_results_r_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_r_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_r_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sr.mif -include $output/$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_r_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_r_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output/$subj\_er.mif -stop -step 0.2 -maxnum 10000000; 
+      echo $subj\_results_l_l_$i\_$j\_$k\_no_ACT
+      tckgen $output/$subj\_FOD_lmax_$i.mif Tractography_dwi/$subj\_results_l_l_$i\_$j\_$k\_no_ACT.tck -number 200 -cutoff $j -angle $k -unidirectional -seed_image $output/$subj\_sl.mif -include $output//$subj\_el.mif -stop -step 0.2 -maxnum 10000000; 
+      
+      echo " "
+    done
+  done
+done
+
+
+
+cd $output/Tractography_dwi
+
+tckedit *_??.tck $subj\_ACT.tck
+tckedit *r_r*_??.tck $subj\_r_r_ACT.tck
+tckedit *r_l*_??.tck $subj\_r_l_ACT.tck
+tckedit *l_r*_??.tck $subj\_l_r_ACT.tck
+tckedit *l_l*_??.tck $subj\_l_l_ACT.tck
+
+tckedit *_no_ACT.tck $subj\_no_ACT.tck
+tckedit *r_r*_no_ACT.tck $subj\_r_r_no_ACT.tck
+tckedit *r_l*_no_ACT.tck $subj\_r_l_no_ACT.tck
+tckedit *l_r*_no_ACT.tck $subj\_l_r_no_ACT.tck
+tckedit *l_l*_no_ACT.tck $subj\_l_l_no_ACT.tck
+
+}
+
+#for i in /home/auguser2016/Projects/Chiasm_RJP_FP/*; do ROIs_tracking ${i: -4}; done
+
+
+ROIs_tracking_dwi fe21
+ROIs_tracking_dwi hw91
+ROIs_tracking_dwi ib57
+ROIs_tracking_dwi kw99
+ROIs_tracking_dwi lw37
+ROIs_tracking_dwi nb30
+ROIs_tracking_dwi ow97
+
+#source 03_life.m $subj
+
+#for r in $subjects; do 
+#  analizuj "$r"
+#  done
+	
+#matlab -nodisplay -r 03_life.m
+
+
diff --git a/06_life.m b/06_life.m
new file mode 100644
index 0000000..5f56da8
--- /dev/null
+++ b/06_life.m
@@ -0,0 +1,59 @@
+% Build the file names for the diffusion data, the anatomical MRI.
+dwiFile       = fullfile('/media/auguser2016/Volume/Test','lw37_aligned_trilin.nii.gz');
+dwiFileRepeat = fullfile('/media/auguser2016/Volume/Test','lw37_aligned_trilin.nii.gz');
+t1File        = fullfile('/media/auguser2016/Volume/Test/anatomy','t1_acpc.nii.gz');
+fgFileName = fullfile('/media/auguser2016/Volume/Test','lw_et.tck')         
+
+% The final connectome and data astructure will be saved with this name:
+feFileName    = 'test_ensemble_tracking';
+
+L = 360; % Discretization parameter
+fe = feConnectomeInit(dwiFile,fgFileName,feFileName,[],dwiFileRepeat,t1File,L,[0,1]);
+
+Niter = 500;
+fe = feSet(fe,'fit',feFitModel(feGet(fe,'model'),feGet(fe,'dsigdemeaned'),'bbnnls',Niter,'preconditioner'));
+
+% Remove non zero weighted fascicles
+fg = feGet(fe,'fibers acpc');
+w = feGet(fe,'fiber weights');
+positive_w = w > 0;
+fg = fgExtract(fg, positive_w, 'keep');
+
+% Use MBA to visualize
+colors     = {[.75 .25 .1]};
+viewCoords = [90,0];
+proportion_to_show = .05;
+threshold_length   = 10;
+slices     = {[18 0 0],[0 -40 0],[0 0 -14]}; % Values in mm from AC 
+
+% Prepare the plot of tract
+fg = rmfield(fg,'coordspace');
+
+% Pick a percentage of fascicles to display (the PN can be too dense for visualization).
+%fibs_indx = RandSample(1:length(fg.fibers),round(length(fg.fibers)*proportion_to_show));
+fg.fibers = fg.fibers(1:2000);
+
+% Display fascicles and anatomy
+fig_h = figure('name','Whole Brain','color','k');
+hold on
+
+% display anatomy
+t1 = niftiRead(t1File);
+%h  = mbaDisplayBrainSlice(t1, slices{1});
+%h  = mbaDisplayBrainSlice(t1, slices{2});
+
+% Disdplay fasciles
+set(gca,'visible','off','ylim',[-108 69],'xlim',[-75 75],'zlim',[-45 78],'Color','w')
+[~, light_h] = mbaDisplayConnectome(fg.fibers,fig_h,colors{1},'single');
+delete(light_h)
+view(viewCoords(1),viewCoords(2))
+light_h = camlight('right');
+lighting phong;
+%set(fig_h,'Units','normalized', 'Position',[0.5 .2 .4 .8]);
+set(gcf,'Color',[1 1 1])
+drawnow
+
+quit
+
+% save figure to disk
+print(fig_h,'my_figure','-dpng','-r600');%'-dpsc2')
diff --git a/06_life_no_ACPC.m b/06_life_no_ACPC.m
new file mode 100644
index 0000000..47dbe01
--- /dev/null
+++ b/06_life_no_ACPC.m
@@ -0,0 +1,79 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% Define participant
+subj ='kw99'
+
+% Define relevant folders
+general_data=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',subj,'/')
+specific_data=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP/',subj,'/')
+current = pwd
+
+cd(general_data)
+
+% Build the file names for the diffusion data, the anatomical MRI.
+dwiFile       = fullfile(strcat(general_data,subj,'_clean_075mm.nii.gz'));
+dwiFileRepeat = fullfile(strcat(general_data,subj,'_clean_075mm.nii.gz'));
+t1File        = fullfile(strcat(general_data,subj,'_075mm_anatomical_coreg2nodif_undist_2.nii.gz'));
+fgFileName = fullfile(strcat(specific_data,'Tractography_dwi/',subj,'_ACT.tck'));
+%fgFileName = fullfile(strcat(specific_data,'Tractography/',subj,'_good.tck'));
+
+% The final connectome and data astructure will be saved with this name:
+feFileName    = 'test_ensemble_tracking';
+
+L = 360; % Discretization parameter
+fe = feConnectomeInit(dwiFile,fgFileName,feFileName,[],dwiFileRepeat,t1File,L,[0,1]);
+
+Niter = 500;
+fe = feSet(fe,'fit',feFitModel(feGet(fe,'model'),feGet(fe,'dsigdemeaned'),'bbnnls',Niter,'preconditioner'));
+
+% Remove non zero weighted fascicles
+fg = feGet(fe,'fibers acpc');
+w = feGet(fe,'fiber weights');
+positive_w = w > 0;
+fg = fgExtract(fg, positive_w, 'keep');
+
+cd(specific_data)
+fgWrite(fg,strcat(subj,'_dwi_filtered.mat'))
+
+% Use MBA to visualize
+colors     = {[.75 .25 .1]};
+viewCoords = [90,0];
+proportion_to_show = .05;
+threshold_length   = 10;
+slices     = {[18 0 0],[0 -40 0],[0 0 -14]}; % Values in mm from AC 
+
+% Prepare the plot of tract
+fg = rmfield(fg,'coordspace');
+
+% Pick a percentage of fascicles to display (the PN can be too dense for visualization).
+%fibs_indx = RandSample(1:length(fg.fibers),round(length(fg.fibers)*proportion_to_show));
+%fg.fibers = fg.fibers(1:1000); 
+
+% Display fascicles and anatomy
+fig_h = figure('name','Whole Brain','color','k');
+hold on
+
+% display anatomy
+%t1 = niftiRead(t1File);
+%h  = mbaDisplayBrainSlice(t1, slices{1});
+%h  = mbaDisplayBrainSlice(t1, slices{2});
+
+% Display fasciles
+set(gca,'visible','off','ylim',[-108 69],'xlim',[-75 75],'zlim',[-45 78],'Color','w')
+[~, light_h] = mbaDisplayConnectome(fg.fibers,fig_h,colors{1},'single');
+delete(light_h)
+view(viewCoords(1),viewCoords(2))
+light_h = camlight('right');
+lighting phong;
+%set(fig_h,'Units','normalized', 'Position',[0.5 .2 .4 .8]);
+set(gcf,'Color',[1 1 1])
+drawnow
+
+%quit
+
+% save figure to disk
+%print(fig_h,'my_figure','-dpng','-r600');%'-dpsc2')
\ No newline at end of file
diff --git a/07_results_evaluation.txt b/07_results_evaluation.txt
new file mode 100644
index 0000000..5cdabdc
--- /dev/null
+++ b/07_results_evaluation.txt
@@ -0,0 +1,59 @@
+Evaluate_anatomy (){
+
+cur_path=$(pwd)
+subj=$1
+
+analysis_folder=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $analysis_folder/ROIs
+cd $analysis_folder/ROIs
+
+mrconvert $analysis_folder/$subj\_start_right.mif $analysis_folder/ROIs/$subj\_start_right.nii
+mrconvert $analysis_folder/$subj\_start_left.mif $analysis_folder/ROIs/$subj\_start_left.nii
+mrconvert $analysis_folder/$subj\_end_right.mif $analysis_folder/ROIs/$subj\_end_right.nii
+mrconvert $analysis_folder/$subj\_end_left.mif $analysis_folder/ROIs/$subj\_end_left.nii
+
+matlab -r "addpath(genpath('/home/auguser2016/Software/vistasoft-master'));addpath(genpath('/home/auguser2016/Software/mba'));addpath(genpath('/home/auguser2016/Software/encode'));dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_start_right.nii','${subj}_start_right');dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_start_left.nii','${subj}_start_left');dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_end_right.nii','${subj}_end_right');dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_end_left.nii','${subj}_end_left')"
+
+cd $cur_path
+}
+
+Evaluate_dwi (){
+
+cur_path=$(pwd)
+subj=$1
+
+analysis_folder=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $analysis_folder/ROIs_dwi
+cd $analysis_folder/ROIs_dwi
+
+mrconvert $analysis_folder/$subj\_sr.mif $analysis_folder/ROIs_dwi/$subj\_start_right.nii
+mrconvert $analysis_folder/$subj\_sl.mif $analysis_folder/ROIs_dwi/$subj\_start_left.nii
+mrconvert $analysis_folder/$subj\_er.mif $analysis_folder/ROIs_dwi/$subj\_end_right.nii
+mrconvert $analysis_folder/$subj\_el.mif $analysis_folder/ROIs_dwi/$subj\_end_left.nii
+
+matlab -r "addpath(genpath('/home/auguser2016/Software/vistasoft-master'));addpath(genpath('/home/auguser2016/Software/mba'));addpath(genpath('/home/auguser2016/Software/encode'));dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_start_right.nii','${subj}_start_right');dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_start_left.nii','${subj}_start_left');dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_end_right.nii','${subj}_end_right');dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_end_left.nii','${subj}_end_left')"
+
+cd $cur_path
+}
+
+
+Evaluate_acpc (){
+
+cur_path=$(pwd)
+subj=$1
+
+analysis_folder=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj/ROIs
+cd $analysis_folder
+
+mrconvert $analysis_folder/$subj\_sr.mif $analysis_folder/$subj\_start_right.nii
+mrconvert $analysis_folder/$subj\_sl.mif $analysis_folder/$subj\_start_left.nii
+mrconvert $analysis_folder/$subj\_er.mif $analysis_folder/$subj\_end_right.nii
+mrconvert $analysis_folder/$subj\_el.mif $analysis_folder/$subj\_end_left.nii
+
+matlab -r "addpath(genpath('/home/auguser2016/Software/vistasoft-master'));addpath(genpath('/home/auguser2016/Software/mba'));addpath(genpath('/home/auguser2016/Software/encode'));dtiImportRoiFromNifti('$analysis_folder/${subj}_start_right.nii','${subj}_start_right');dtiImportRoiFromNifti('$analysis_folder/${subj}_start_left.nii','${subj}_start_left');dtiImportRoiFromNifti('$analysis_folder/${subj}_end_right.nii','${subj}_end_right');dtiImportRoiFromNifti('$analysis_folder/${subj}_end_left.nii','${subj}_end_left')"
+
+cd $cur_path
+}
+
+
+Evaluate_acpc $1
diff --git a/07_results_evaluation.txt~ b/07_results_evaluation.txt~
new file mode 100644
index 0000000..b6f9509
--- /dev/null
+++ b/07_results_evaluation.txt~
@@ -0,0 +1,39 @@
+Evaluate_anatomy (){
+
+cur_path=$(pwd)
+subj=$1
+
+analysis_folder=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $analysis_folder/ROIs
+cd $analysis_folder/ROIs
+
+mrconvert $analysis_folder/$subj\_start_right.mif $analysis_folder/ROIs/$subj\_start_right.nii
+mrconvert $analysis_folder/$subj\_start_left.mif $analysis_folder/ROIs/$subj\_start_left.nii
+mrconvert $analysis_folder/$subj\_end_right.mif $analysis_folder/ROIs/$subj\_end_right.nii
+mrconvert $analysis_folder/$subj\_end_left.mif $analysis_folder/ROIs/$subj\_end_left.nii
+
+matlab -r "addpath(genpath('/home/auguser2016/Software/vistasoft-master'));addpath(genpath('/home/auguser2016/Software/mba'));addpath(genpath('/home/auguser2016/Software/encode'));dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_start_right.nii','${subj}_start_right');dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_start_left.nii','${subj}_start_left');dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_end_right.nii','${subj}_end_right');dtiImportRoiFromNifti('$analysis_folder/ROIs/${subj}_end_left.nii','${subj}_end_left')"
+
+cd $cur_path
+}
+
+Evaluate_dwi (){
+
+cur_path=$(pwd)
+subj=$1
+
+analysis_folder=/home/auguser2016/Projects/Chiasm_RJP_FP/$subj
+mkdir $analysis_folder/ROIs_dwi
+cd $analysis_folder/ROIs_dwi
+
+mrconvert $analysis_folder/$subj\_sr.mif $analysis_folder/ROIs_dwi/$subj\_start_right.nii
+mrconvert $analysis_folder/$subj\_sl.mif $analysis_folder/ROIs_dwi/$subj\_start_left.nii
+mrconvert $analysis_folder/$subj\_er.mif $analysis_folder/ROIs_dwi/$subj\_end_right.nii
+mrconvert $analysis_folder/$subj\_el.mif $analysis_folder/ROIs_dwi/$subj\_end_left.nii
+
+matlab -r "addpath(genpath('/home/auguser2016/Software/vistasoft-master'));addpath(genpath('/home/auguser2016/Software/mba'));addpath(genpath('/home/auguser2016/Software/encode'));dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_start_right.nii','${subj}_start_right');dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_start_left.nii','${subj}_start_left');dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_end_right.nii','${subj}_end_right');dtiImportRoiFromNifti('$analysis_folder/ROIs_dwi/${subj}_end_left.nii','${subj}_end_left')"
+
+cd $cur_path
+}
+
+Evaluate_anatomy $1
diff --git a/08_psychophysics.sh b/08_psychophysics.sh
new file mode 100644
index 0000000..0d606fe
--- /dev/null
+++ b/08_psychophysics.sh
@@ -0,0 +1,19 @@
+generate_images {
+
+subj=$1
+
+#Open T1 generate_images
+
+# Generate random rotation matrix slightly tilting generated images (3 degrees of freedom)
+
+# Apply matrix to data
+
+# Load data into mrtrix
+
+# Select at random one point (z coordinate of intersecting plane)
+
+# Capture images
+
+# Repeat
+
+}
diff --git a/Copy_of_06_life_ACPC.m b/Copy_of_06_life_ACPC.m
new file mode 100644
index 0000000..9f2ea5f
--- /dev/null
+++ b/Copy_of_06_life_ACPC.m
@@ -0,0 +1,79 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% Define participant
+subj ='uf97'
+
+% Define relevant folders
+general_data=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',subj,'/')
+specific_data=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',subj,'/')
+current = pwd
+
+cd(general_data)
+
+% Build the file names for the diffusion data, the anatomical MRI.
+dwiFile       = fullfile(strcat(specific_data,subj,'_clean_150mm_aligned_trilin_noMEC.nii.gz'));
+dwiFileRepeat = fullfile(strcat(specific_data,subj,'_clean_150mm_aligned_trilin_noMEC.nii.gz'));
+t1File        = fullfile(strcat(specific_data,subj,'_t1_acpc.nii.gz'));
+fgFileName = fullfile(strcat(specific_data,'Tractography/',subj,'_ACT.tck'));
+%fgFileName = fullfile(strcat(specific_data,'Tractography/',subj,'_good.tck'));
+
+% The final connectome and data astructure will be saved with this name:
+feFileName    = 'test_ensemble_tracking';
+
+L = 360; % Discretization parameter
+fe = feConnectomeInit(dwiFile,fgFileName,feFileName,[],dwiFileRepeat,t1File,L,[0,1]);
+
+Niter = 500;
+fe = feSet(fe,'fit',feFitModel(feGet(fe,'model'),feGet(fe,'dsigdemeaned'),'bbnnls',Niter,'preconditioner'));
+
+% Remove non zero weighted fascicles
+fg = feGet(fe,'fibers acpc');
+w = feGet(fe,'fiber weights');
+positive_w = w > 0;
+fg = fgExtract(fg, positive_w, 'keep');
+
+cd(specific_data)
+fgWrite(fg,strcat(subj,'_acpc_filtered.mat'))
+
+% Use MBA to visualize
+colors     = {[.75 .25 .1]};
+viewCoords = [90,0];
+proportion_to_show = .05;
+threshold_length   = 10;
+slices     = {[18 0 0],[0 -40 0],[0 0 -14]}; % Values in mm from AC 
+
+% Prepare the plot of tract
+fg = rmfield(fg,'coordspace');
+
+% Pick a percentage of fascicles to display (the PN can be too dense for visualization).
+%fibs_indx = RandSample(1:length(fg.fibers),round(length(fg.fibers)*proportion_to_show));
+%fg.fibers = fg.fibers(1:1000); 
+
+% Display fascicles and anatomy
+fig_h = figure('name','Whole Brain','color','k');
+hold on
+
+% display anatomy
+%t1 = niftiRead(t1File);
+%h  = mbaDisplayBrainSlice(t1, slices{1});
+%h  = mbaDisplayBrainSlice(t1, slices{2});
+
+% Display fasciles
+set(gca,'visible','off','ylim',[-108 69],'xlim',[-75 75],'zlim',[-45 78],'Color','w')
+[~, light_h] = mbaDisplayConnectome(fg.fibers,fig_h,colors{1},'single');
+delete(light_h)
+view(viewCoords(1),viewCoords(2))
+light_h = camlight('right');
+lighting phong;
+%set(fig_h,'Units','normalized', 'Position',[0.5 .2 .4 .8]);
+set(gcf,'Color',[1 1 1])
+drawnow
+
+%quit
+
+% save figure to disk
+%print(fig_h,'my_figure','-dpng','-r600');%'-dpsc2')
\ No newline at end of file

From 1a15cd2f93209e89d44cf3e7159ecdc43d3055fc Mon Sep 17 00:00:00 2001
From: franco <frakkopesto@gmail.com>
Date: Fri, 2 Jun 2017 21:34:50 +0200
Subject: [PATCH 7/7] Correcting erroneous grad_table

---
 01_prepare_for_acpc.sh             | 21 ++++++++
 02_t1_and_dwi_to_acpc.m            | 72 ++++++++++++++++++++++++++
 03_check_and_segment_acpc.sh       | 37 ++++++++++++++
 04_postprocess.sh                  | 24 +++++++--
 04_postprocess.sh~                 | 24 +++++++--
 Copy_of_06_life_ACPC.m             |  2 +-
 old_03_t1_and_dwi_to_acpc.m        | 51 +++++++++++++++++++
 option_01_check_preprocessing.sh   | 81 ++++++++++++++++++++++++++++++
 option_03_working_on_original_lw.m | 49 ++++++++++++++++++
 9 files changed, 350 insertions(+), 11 deletions(-)
 create mode 100644 01_prepare_for_acpc.sh
 create mode 100644 02_t1_and_dwi_to_acpc.m
 create mode 100644 03_check_and_segment_acpc.sh
 create mode 100644 old_03_t1_and_dwi_to_acpc.m
 create mode 100644 option_01_check_preprocessing.sh
 create mode 100644 option_03_working_on_original_lw.m

diff --git a/01_prepare_for_acpc.sh b/01_prepare_for_acpc.sh
new file mode 100644
index 0000000..ca1d232
--- /dev/null
+++ b/01_prepare_for_acpc.sh
@@ -0,0 +1,21 @@
+ACPC_preparation () {
+
+	# Registration to ACPC space requires preprocessed DWI image in .nii (or .nii.gz) format with corresponding bvecs and bvals. T1 image in ACPC space will be prepared separately
+
+	# Defining data set and its' path
+	a=${1::-6}
+	data=/home/auguser2016/dMRI_DATA
+	high_res=PREPROCESSED_DATA/0.75mm_iso/$a
+
+	# Obtain bvecs and bvals
+	mrinfo $data/$high_res/$a\_clean_075mm.mif -export_grad_fsl $data/$high_res/$a\_bvecs.bvecs $data/$high_res/$a\_bvals.bvals
+
+	# Transform DW in .mif into .nii.gz
+	mrconvert $data/$high_res/$a\_clean_075mm.mif $data/$high_res/$a\_clean_075mm.nii.gz
+}
+
+# List of all data_sets used in studies
+list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
+
+# As during processing of each data set full resources are used, lining them up is an effective approach
+for i in ${list[@]}; do ACPC_preparation $i; done
diff --git a/02_t1_and_dwi_to_acpc.m b/02_t1_and_dwi_to_acpc.m
new file mode 100644
index 0000000..07f4074
--- /dev/null
+++ b/02_t1_and_dwi_to_acpc.m
@@ -0,0 +1,72 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% ACPC registration for T1 in each data set performed manually
+% Done manually
+
+% Perform Diffusion Imaging Processing for all data sets
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/
+subjects=dir
+
+for i=3:size(subjects,1)
+    
+    id=subjects(i).name
+    %id='hw91'
+    % Prepare data in form acceptable by dtiInit
+    
+    % ACPC registerred T1 image
+    anatomy=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_t1_acpc.nii.gz')
+    
+    % Diffusion Data (motion, eddy and geometrical distortions corrected)
+    dwi=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_clean_150mm.nii.gz')
+    
+    % Bvecs and bvals obtained from corrected DW images
+    bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvecs.bvecs')
+    bvals=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvals.bvals')
+    
+    %bvecs_rot = dlmread(bvecs);
+    %bvecs_rot(1,:) = -bvecs_rot(1,:);
+    %dlmwrite(strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id1,'/',id,'_bvecs_rot.bvecs'),bvecs_rot)
+    %bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id1,'/',id,'_bvecs_rot.bvecs')
+    
+    %bvecs_rot = dlmread(bvecs);
+    %bvecs_rot(2,:) z= -bvecs_rot(2,:);
+    %dlmwrite(strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id1,'/',id,'_bvecs_rot.bvecs'),bvecs_rot)
+    %bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id1,'/',id,'_bvecs_rot.bvecs')
+  
+% %przypomnienie, że bveci to ważna sprawa i możliwe, że mam filpa na osi y
+%     bvecs_rot = dlmread(bvecs);
+%     bvecs_rot(2,:)=-bvecs_rot(2,:);
+%     dlmwrite(strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvecs_rot.bvecs'), bvecs_rot)
+    
+    % Output directory
+    output=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/')
+    
+    % Set up dtiInit paramters specific for our study
+    dwParams = dtiInitParams;
+    dwParams.rotateBvecsWithRx = 1;
+    dwParams.rotateBvecsWithCanXform = 1;
+    dwParams.bvecsFile = fullfile(bvecs);
+    dwParams.bvalsFile = fullfile(bvals);
+    dwParams.eddyCorrect = -1;
+    dwParams.dwOutMm = [0.75 0.75 0.75]; % change this to 1.5 and process 0.75 anyway
+    %dwParams.dwOutMm = [1.5 1.5 1.5];
+    dwParams.phaseEncodeDir = 2;
+    dwParams.outDir=output
+    %dwParams.outDir = fullfile(pwd,'dtiInitPreprocessed');
+
+    % Start Diffusion Imaging preprocessing.
+    [dt6FileName, outBaseDir] = dtiInit(dwi,...
+                                        anatomy, ...
+                                        dwParams); 
+    
+     mrtrix_bfileFromBvecs(strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_clean_150mm_aligned_trilin_noMEC.bvecs'),strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_clean_150mm_aligned_trilin_noMEC.bvals'),strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_mrtrix_grad_table.b'))
+
+     end
+
+     %pathToScript = fullfile('/media/auguser2016/Volume/Test/chiasm','04_postprocess.sh'); 
+     %cmdStr = sprintf('%s', pathToScript);
+     %system(cmdStr);
diff --git a/03_check_and_segment_acpc.sh b/03_check_and_segment_acpc.sh
new file mode 100644
index 0000000..c7e7aab
--- /dev/null
+++ b/03_check_and_segment_acpc.sh
@@ -0,0 +1,37 @@
+Check_acpc () {
+
+subj=$1
+
+analysis=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+
+# Compare coregisterred DW image with anatomy in acpc space
+#mrview $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_t1_acpc.nii.gz
+
+# Compare DW images before and after registration
+#mrview $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.nii.gz /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_clean_075mm.mif
+
+# Compare their bvecs
+#gedit $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.bvecs /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_bvecs.bvecs
+
+# Compare their bvals
+#gedit $analysis/$subj\_clean_075mm_aligned_trilin_noMEC.bvals /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj/$subj\_bvals.bvals
+
+# for ACPC registration
+# Perform segmentation of T1 image in ACPC space into WM, GM, subGM, CSF and potential pathological tissue
+5ttgen fsl $analysis/$subj\_t1_acpc.nii.gz $analysis/$subj\_t1_acpc_5tt.nii.gz
+
+# Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+#mrview $analysis/$subj\_t1_acpc_5tt.nii.gz -colourmap 3 -overlay.load $analysis/$subj\_t1_acpc.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $analysis/$subj\_5tt_patch.mif
+
+#5ttedit $analysis/$subj\_t1_acpc_5tt.nii.gz -wm $analysis/$subj\_5tt_patch.mif $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -force
+
+#while true; do
+#  mrview $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -colourmap 3 -overlay.load $analysis/$subj\_t1_acpc.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $analysis/$subj\_5tt_patch.mif
+#  5ttedit $analysis/$subj\_t1_acpc_5tt.nii.gz -wm $analysis/$subj\_5tt_patch.mif $analysis/$subj\_t1_acpc_5tt_modified.nii.gz -force
+#done
+
+}
+
+#for i in /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/*; do Check_acpc ${i: -4}; done
+
+Check_acpc $1
diff --git a/04_postprocess.sh b/04_postprocess.sh
index 57463de..a1cf419 100644
--- a/04_postprocess.sh
+++ b/04_postprocess.sh
@@ -1,25 +1,38 @@
+ #!/bin/bash
+
 General_postprocessing () {
 
-subj=${1::-6}
+subj=${1}
 
 analysis=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+#analysis=/home/auguser2016/Projects/hw91_canxform
 
-dwi2mask $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_mask.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+dwi2mask $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_mask.nii.gz -grad $analysis/$subj\_mrtrix_grad_table.b
 
 # Estimating single fibre response (SFR) for lmax=6
-dwi2response tournier $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_SFR.txt -shell 1600 -lmax 6 -mask $analysis/$subj\_acpc_mask.nii.gz  -voxels $analysis/$subj\_acpc_SFR_voxels.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+dwi2response tournier $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_SFR.txt -shell 1600 -lmax 6 -mask $analysis/$subj\_acpc_mask.nii.gz  -voxels $analysis/$subj\_acpc_SFR_voxels.nii.gz -grad $analysis/$subj\_mrtrix_grad_table.b
 
 # Estimation of Fiber Orientation Distribution function for 3 lmax
 for lmax in 8 10 12; do  
-  dwiextract $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals - | dwi2fod msmt_csd - $analysis/$subj\_acpc_SFR.txt -lmax $lmax $analysis/$subj\_acpc_FOD_lmax_$lmax.mif -mask $analysis/$subj\_acpc_mask.nii.gz 
+  dwiextract $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz -grad $analysis/$subj\_mrtrix_grad_table.b - | dwi2fod msmt_csd - $analysis/$subj\_acpc_SFR.txt -lmax $lmax $analysis/$subj\_acpc_FOD_lmax_$lmax.mif -mask $analysis/$subj\_acpc_mask.nii.gz 
 done
 }
 
+current=$(pwd)
+
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC
+for i in */; do
+	General_postprocessing ${i::-1};
+done
+
+cd $current
+
 
+'''
 # List of all data_sets used in studies
 list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
 
-list=(uf97_1072/) #ow93_0974/ )
+list=(hw91_some/) #ow93_0974/ )
 
 
 # This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
@@ -46,3 +59,4 @@ for i in ${list[@]:27:30}; do General_postprocessing $i & done
 wait
 for i in ${list[@]:30:33}; do General_postprocessing $i & done
 wait
+'''
diff --git a/04_postprocess.sh~ b/04_postprocess.sh~
index 645b497..a1cf419 100644
--- a/04_postprocess.sh~
+++ b/04_postprocess.sh~
@@ -1,25 +1,38 @@
+ #!/bin/bash
+
 General_postprocessing () {
 
-subj=${1::-6}
+subj=${1}
 
 analysis=/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/$subj
+#analysis=/home/auguser2016/Projects/hw91_canxform
 
-dwi2mask $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_mask.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+dwi2mask $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_mask.nii.gz -grad $analysis/$subj\_mrtrix_grad_table.b
 
 # Estimating single fibre response (SFR) for lmax=6
-dwi2response tournier $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_SFR.txt -shell 1600 -lmax 6 -mask $analysis/$subj\_acpc_mask.nii.gz  -voxels $analysis/$subj\_acpc_SFR_voxels.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals
+dwi2response tournier $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz $analysis/$subj\_acpc_SFR.txt -shell 1600 -lmax 6 -mask $analysis/$subj\_acpc_mask.nii.gz  -voxels $analysis/$subj\_acpc_SFR_voxels.nii.gz -grad $analysis/$subj\_mrtrix_grad_table.b
 
 # Estimation of Fiber Orientation Distribution function for 3 lmax
 for lmax in 8 10 12; do  
-  dwiextract $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz -fslgrad $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvecs $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.bvals - | dwi2fod msmt_csd - $analysis/$subj\_acpc_SFR.txt -lmax $lmax $analysis/$subj\_acpc_FOD_lmax_$lmax.mif -mask $analysis/$subj\_acpc_mask.nii.gz 
+  dwiextract $analysis/$subj\_clean_150mm_aligned_trilin_noMEC.nii.gz -grad $analysis/$subj\_mrtrix_grad_table.b - | dwi2fod msmt_csd - $analysis/$subj\_acpc_SFR.txt -lmax $lmax $analysis/$subj\_acpc_FOD_lmax_$lmax.mif -mask $analysis/$subj\_acpc_mask.nii.gz 
 done
 }
 
+current=$(pwd)
+
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC
+for i in */; do
+	General_postprocessing ${i::-1};
+done
+
+cd $current
+
 
+'''
 # List of all data_sets used in studies
 list=(fe21_1325/ hw91_0844/ ib57_0731/ kw99_0633/ lw37_0977/ nb30_1185/ ow93_0974/ ps94_1516/ rx88_1234/ sj22_1218/ ta14_1065/ tq63_1214/ xs62_1217/ xn78_1085/ uh47_1309/ uf97_1072/ ow93_0974/ )
 
-list=(uh47_1309/) #uf97_1072/ ow93_0974/ )
+list=(hw91_some/) #ow93_0974/ )
 
 
 # This way 4 sets are processed at once - we can't process all at once due to RAM usage, however preprocessing one at a time is ineffective because e.g. eddy from dwipreproc is using only one core. There is a version of eddy operating on multicore processors, but it's not running on this machine
@@ -46,3 +59,4 @@ for i in ${list[@]:27:30}; do General_postprocessing $i & done
 wait
 for i in ${list[@]:30:33}; do General_postprocessing $i & done
 wait
+'''
diff --git a/Copy_of_06_life_ACPC.m b/Copy_of_06_life_ACPC.m
index 9f2ea5f..9771a27 100644
--- a/Copy_of_06_life_ACPC.m
+++ b/Copy_of_06_life_ACPC.m
@@ -5,7 +5,7 @@
 addpath(genpath('/home/auguser2016/Software/encode'))
 
 % Define participant
-subj ='uf97'
+subj ='fe21'
 
 % Define relevant folders
 general_data=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',subj,'/')
diff --git a/old_03_t1_and_dwi_to_acpc.m b/old_03_t1_and_dwi_to_acpc.m
new file mode 100644
index 0000000..b1db325
--- /dev/null
+++ b/old_03_t1_and_dwi_to_acpc.m
@@ -0,0 +1,51 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% ACPC registration for T1 in each data set performed manually
+% Done manually
+
+% Perform Diffusion Imaging Processing for all data sets
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/
+subjects=dir
+
+for i=5:size(subjects,1)
+    
+    id=subjects(i).name
+    %id='fe21'
+    % Prepare data in form acceptable by dtiInit
+    
+    % ACPC registerred T1 image
+    anatomy=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_t1_acpc.nii.gz')
+    
+    % Diffusion Data (motion, eddy and geometrical distortions corrected)
+    dwi=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'_clean_075mm.nii.gz')
+    %dwi=strcat('/media/auguser2016/Volume/Test/lw37.nii.gz')
+    
+    % Bvecs and bvals obtained from corrected DW images
+    bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'_bvecs.bvecs')
+    bvals=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/',id,'/',id,'_bvals.bvals')
+  
+    % Output directory
+    output=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/')
+    
+    % Set up dtiInit paramters specific for our study
+    dwParams = dtiInitParams;
+    dwParams.rotateBvecsWithRx = 1;
+    dwParams.rotateBvecsWithCanXform = 0;
+    dwParams.bvecsFile = fullfile(bvecs);
+    dwParams.bvalsFile = fullfile(bvals);
+    dwParams.eddyCorrect = -1;
+    dwParams.dwOutMm = [0.75 0.75 0.75]; % change this to 1.5 and process 0.75 anyway
+    %dwParams.dwOutMm = [1.5 1.5 1.5];
+    dwParams.phaseEncodeDir = 2;
+    dwParams.outDir=output
+    %dwParams.outDir = fullfile(pwd,'dtiInitPreprocessed');
+
+    % Start Diffusion Imaging preprocessing.
+    [dt6FileName, outBaseDir] = dtiInit(dwi,...
+                                        anatomy, ...
+                                        dwParams); 
+end
diff --git a/option_01_check_preprocessing.sh b/option_01_check_preprocessing.sh
new file mode 100644
index 0000000..8b717c0
--- /dev/null
+++ b/option_01_check_preprocessing.sh
@@ -0,0 +1,81 @@
+Check_preprocessing () {
+
+subj=$1
+
+low_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/$subj
+high_res=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+
+# View denoising maps. The less anatomical structures are visible the better
+mrview $low_res/Temporal/Distortions/$subj\_series*
+
+# Compare DWI before and after denoising for each encoding direction
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*AP_denoised.mif
+mrview $low_res/Temporal/*PA.mif $low_res/Temporal/*PA_denoised.mif
+
+# Compare mrtrix gradient for corrected DWI with original gradient table
+mrinfo $low_res/Temporal/$subj\_*AP_denoised.mif -export_grad_fsl $low_res/Temporal/bvecs $low_res/Temporal/bvals
+gedit $low_res/Temporal/bvecs &
+gedit $low_res/Temporal/Distortions/$subj\_gradients &
+gedit /home/auguser2016/dMRI_DATA/RAW_DATA/$subj*/s*/*ep2d*/*.bvec
+rm $low_res/Temporal/bvecs $low_res/Temporal/bvals
+
+# Compare DWI before and after dwipreproc
+mrview $low_res/Temporal/*AP.mif $low_res/Temporal/*PA.mif $low_res/Temporal/$subj\_denoised_preproc.mif
+
+# View mask used for bias field correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif -overlay.load  $low_res/$subj\_clean_150mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View bias field
+mrview $low_res/Temporal/Distortions/$subj\_bias_field.mif
+
+# View DWI before and after bias correction
+mrview $low_res/Temporal/$subj\_denoised_preproc.mif $low_res/$subj\_clean_150mm.mif
+
+# View normal and upsampled images
+mrview $low_res/$subj\_clean_150mm.mif $high_res/$subj\_clean_075mm.mif
+
+# View upsampled mask
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load  $high_res/$subj\_clean_075mm_mask.mif -overlay.opacity 0.2 -overlay.colourmap 3
+
+# View SFR estimation voxels
+mrview $high_res/$subj\_clean_075mm.mif -overlay.load $high_res/Temporal/$subj\_clean_075mm_SFR_voxels.mif
+
+# View SFR
+shview $high_res/$subj\_clean_075mm_SFR.txt
+
+# View anatomical image overlaid on DWI
+mrview $high_res/$subj\_clean_075mm_FOD.mif $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz
+
+# View results of bet2
+mrview $high_res/$subj\_anatomical.nii.gz -overlay.load $high_res/Temporal/$subj\_anatomical_brain.nii.gz -overlay.opacity 0.3
+
+# View segmentation
+mrview $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.load $high_res/$subj\_075mm_5tt.nii.gz -overlay.opacity 0.3
+
+# Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+mrview $high_res/$subj\_075mm_5tt.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+
+5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+
+while true; do
+  mrview $high_res/$subj\_5tt_for_act_modified.nii.gz -colourmap 3 -overlay.load $high_res/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $high_res/$subj\_5tt_patch.mif
+  5ttedit $high_res/$subj\_075mm_5tt.nii.gz -wm $high_res/$subj\_5tt_patch.mif $high_res/$subj\_5tt_for_act_modified.nii.gz -force
+done
+
+#data=/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/0.75mm_iso/$subj
+
+### Correct WM segmentation in chiasm - modify opened ROI and close mrview. Modified WM segmentation image will be shown - repeat previous steps until satisfactory result is obtained. Terminate console to finish process
+#mrview $data/$subj\_075mm_5tt.nii.gz -colourmap 3 -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $data/$subj\_5tt_patch.mif
+
+#5ttedit $data/$subj\_075mm_5tt.nii.gz -wm $data/$subj\_5tt_patch.mif $data/$subj\_075mm_5tt_modify.nii.gz -force
+
+#while true; do
+#  mrview $data/$subj\_075mm_5tt_modify.nii.gz -colourmap 3 -overlay.load $data/$subj\_075mm_anatomical_coreg2nodif_undist_2.nii.gz -overlay.colourmap 0 -overlay.opacity 0.8 -roi.load $data/$subj\_5tt_patch.mif
+#  5ttedit $data/$subj\_075mm_5tt.nii.gz -wm $data/$subj\_5tt_patch.mif $data/$subj\_075mm_5tt_modify.nii.gz -force
+#done
+
+}
+
+#for i in /home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/*; do Check_preprocessing ${i: -4}; done
+
+Check_preprocessing $1
diff --git a/option_03_working_on_original_lw.m b/option_03_working_on_original_lw.m
new file mode 100644
index 0000000..6ae4082
--- /dev/null
+++ b/option_03_working_on_original_lw.m
@@ -0,0 +1,49 @@
+% Add required folders to path
+addpath(genpath('/home/auguser2016/Software/spm12'))
+addpath(genpath('/home/auguser2016/Software/vistasoft-master'))
+addpath(genpath('/home/auguser2016/Software/mba'))
+addpath(genpath('/home/auguser2016/Software/encode'))
+
+% ACPC registration for T1 in each data set performed manually
+% Done manually
+
+% Perform Diffusion Imaging Processing for all data sets
+cd /home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/
+subjects=dir
+
+for i=5:size(subjects,1)
+    
+    id=subjects(i).name
+    % Prepare data in form acceptable by dtiInit
+    
+    % ACPC registerred T1 image
+    anatomy=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/',id,'_t1_acpc.nii.gz')
+    
+    % Diffusion Data (motion, eddy and geometrical distortions corrected)
+    dwi=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_clean_150mm.nii.gz')
+    
+    % Bvecs and bvals obtained from corrected DW images
+    bvecs=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvecs.bvecs')
+    bvals=strcat('/home/auguser2016/dMRI_DATA/PREPROCESSED_DATA/1.5mm_iso/',id,'/',id,'_bvals.bvals')
+  
+    % Output directory
+    output=strcat('/home/auguser2016/Projects/Chiasm_RJP_FP_ACPC/',id,'/')
+    
+    % Set up dtiInit paramters specific for our study
+    dwParams = dtiInitParams;
+    dwParams.rotateBvecsWithRx = 1;
+    dwParams.rotateBvecsWithCanXform = 0;
+    dwParams.bvecsFile = fullfile(bvecs);
+    dwParams.bvalsFile = fullfile(bvals);
+    dwParams.eddyCorrect = -1;
+    dwParams.dwOutMm = [0.75 0.75 0.75]; % change this to 1.5 and process 0.75 anyway
+    %dwParams.dwOutMm = [1.5 1.5 1.5];
+    dwParams.phaseEncodeDir = 2;
+    dwParams.outDir=output
+    %dwParams.outDir = fullfile(pwd,'dtiInitPreprocessed');
+
+    % Start Diffusion Imaging preprocessing.
+    [dt6FileName, outBaseDir] = dtiInit(dwi,...
+                                        anatomy, ...
+                                        dwParams); 
+end