diff --git a/multi_subject/process_data.sh b/multi_subject/process_data.sh
index e7121f5..e21a01c 100755
--- a/multi_subject/process_data.sh
+++ b/multi_subject/process_data.sh
@@ -45,21 +45,21 @@ label_if_does_not_exist() {
   #     - If it doesn't, perform automatic labeling.
   #   This allows you to add manual labels on a subject-by-subject basis without disrupting the pipeline.
   ###
-  local file="$1"
-  local file_seg="$2"
+  local file="${1}"
+  local file_seg="${2}"
   # Update global variable with segmentation file name
-  FILELABEL="${file}_labels"
-  FILELABELMANUAL="${PATH_DATA}/derivatives/labels/${SUBJECT}/anat/${FILELABEL}-manual.nii.gz"
-  echo "Looking for manual label: $FILELABELMANUAL"
-  if [[ -e $FILELABELMANUAL ]]; then
+  FILELABEL="${file}"_labels
+  FILELABELMANUAL="${PATH_DATA}"/derivatives/labels/"${SUBJECT}"/anat/"${FILELABEL}"-manual.nii.gz
+  echo "Looking for manual label: ${FILELABELMANUAL}"
+  if [[ -e "${FILELABELMANUAL}" ]]; then
     echo "Found! Using manual labels."
-    rsync -avzh $FILELABELMANUAL ${FILELABEL}.nii.gz
+    rsync -avzh "${FILELABELMANUAL}" "${FILELABEL}".nii.gz
   else
     echo "Not found. Proceeding with automatic labeling."
     # Generate labeled segmentation
-    sct_label_vertebrae -i ${file}.nii.gz -s ${file_seg}.nii.gz -c t2 -qc "${PATH_QC}" -qc-subject "${SUBJECT}"
+    sct_label_vertebrae -i "${file}".nii.gz -s "${file_seg}".nii.gz -c t2 -qc "${PATH_QC}" -qc-subject "${SUBJECT}"
     # Create labels in the cord at C3 and C5 mid-vertebral levels
-    sct_label_utils -i ${file_seg}_labeled.nii.gz -vert-body 3,5 -o ${FILELABEL}.nii.gz
+    sct_label_utils -i "${file_seg}"_labeled.nii.gz -vert-body 3,5 -o "${FILELABEL}".nii.gz
   fi
 }
 
@@ -70,21 +70,21 @@ segment_if_does_not_exist() {
   #    - If it doesn't, perform automatic spinal cord segmentation.
   #  This allows you to add manual segmentations on a subject-by-subject basis without disrupting the pipeline.
   ###
-  local file="$1"
-  local contrast="$2"
+  local file="${1}"
+  local contrast="${2}"
   # Update global variable with segmentation file name
-  FILESEG="${file}_seg"
-  FILESEGMANUAL="${PATH_DATA}/derivatives/labels/${SUBJECT}/anat/${FILESEG}-manual.nii.gz"
+  FILESEG="${file}"_seg
+  FILESEGMANUAL="${PATH_DATA}"/derivatives/labels/"${SUBJECT}"/anat/"${FILESEG}"-manual.nii.gz
   echo
-  echo "Looking for manual segmentation: $FILESEGMANUAL"
-  if [[ -e $FILESEGMANUAL ]]; then
+  echo "Looking for manual segmentation: ${FILESEGMANUAL}"
+  if [[ -e "${FILESEGMANUAL}" ]]; then
     echo "Found! Using manual segmentation."
-    rsync -avzh $FILESEGMANUAL ${FILESEG}.nii.gz
-    sct_qc -i ${file}.nii.gz -s ${FILESEG}.nii.gz -p sct_deepseg_sc -qc ${PATH_QC} -qc-subject ${SUBJECT}
+    rsync -avzh "${FILESEGMANUAL}" "${FILESEG}".nii.gz
+    sct_qc -i "${file}".nii.gz -s "${FILESEG}".nii.gz -p sct_deepseg_sc -qc "${PATH_QC}" -qc-subject "${SUBJECT}"
   else
     echo "Not found. Proceeding with automatic segmentation."
     # Segment spinal cord
-    sct_deepseg_sc -i ${file}.nii.gz -c $contrast -qc ${PATH_QC} -qc-subject ${SUBJECT}
+    sct_deepseg_sc -i "${file}".nii.gz -c "${contrast}" -qc "${PATH_QC}" -qc-subject "${SUBJECT}"
   fi
 }
 
@@ -93,24 +93,24 @@ segment_if_does_not_exist() {
 # ======================================================================================================================
 
 # Retrieve input params
-SUBJECT=$1
+SUBJECT="${1}"
 
 # get starting time:
-start=`date +%s`
+start="$(date +%s)"
 
 # Display useful info for the log, such as SCT version, RAM and CPU cores available
 sct_check_dependencies -short
 
 # Go to folder where data will be copied and processed
-cd $PATH_DATA_PROCESSED
+cd "${PATH_DATA_PROCESSED}"
 # Copy source images
-rsync -avzh $PATH_DATA/$SUBJECT .
+rsync -avzh "${PATH_DATA}"/"${SUBJECT}" .
 
 
 # T2w
 # ======================================================================================================================
-cd "${SUBJECT}/anat/"
-file_t2="${SUBJECT}_T2w"
+cd "${SUBJECT}"/anat/
+file_t2="${SUBJECT}"_T2w
 # Segment spinal cord (only if it does not exist)
 segment_if_does_not_exist "${file_t2}" "t2"
 file_t2_seg="${FILESEG}"
@@ -118,36 +118,36 @@ file_t2_seg="${FILESEG}"
 label_if_does_not_exist "${file_t2}" "${file_t2_seg}"
 file_label="${FILELABEL}"
 # Register to template
-sct_register_to_template -i "${file_t2}.nii.gz" -s "${file_t2_seg}.nii.gz" -l "${file_label}.nii.gz" -c t2 \
+sct_register_to_template -i "${file_t2}".nii.gz -s "${file_t2_seg}".nii.gz -l "${file_label}".nii.gz -c t2 \
                          -param step=1,type=seg,algo=centermassrot:step=2,type=im,algo=syn,iter=5,slicewise=1,metric=CC,smooth=0 \
                          -qc "${PATH_QC}"
 # Warp template
 # Note: we don't need the white matter atlas at this point, therefore use flag "-a 0"
-sct_warp_template -d "${file_t2}.nii.gz" -w warp_template2anat.nii.gz -a 0 -ofolder label_T2w -qc "${PATH_QC}"
+sct_warp_template -d "${file_t2}".nii.gz -w warp_template2anat.nii.gz -a 0 -ofolder label_T2w -qc "${PATH_QC}"
 # Compute average CSA between C2 and C3 levels (append across subjects)
-sct_process_segmentation -i "${file_t2_seg}.nii.gz" -vert 2:3 -vertfile label_T2w/template/PAM50_levels.nii.gz \
-                         -o "${PATH_RESULTS}/CSA.csv" -append 1 -qc "${PATH_QC}"
+sct_process_segmentation -i "${file_t2_seg}".nii.gz -vert 2:3 -vertfile label_T2w/template/PAM50_levels.nii.gz \
+                         -o "${PATH_RESULTS}"/CSA.csv -append 1 -qc "${PATH_QC}"
 
 # MT
 # ======================================================================================================================
-file_mt1="${SUBJECT}_acq-MTon_MTS"
-file_mt0="${SUBJECT}_acq-MToff_MTS"
+file_mt1="${SUBJECT}"_acq-MTon_MTS
+file_mt0="${SUBJECT}"_acq-MToff_MTS
 # Segment spinal cord
 segment_if_does_not_exist "${file_mt1}" "t2s"
-file_mt1_seg=$FILESEG
+file_mt1_seg="${FILESEG}"
 # Create mask
-sct_create_mask -i "${file_mt1}.nii.gz" -p centerline,"${file_mt1_seg}.nii.gz" -size 45mm
+sct_create_mask -i "${file_mt1}".nii.gz -p centerline,"${file_mt1_seg}".nii.gz -size 45mm
 # Crop data for faster processing
-sct_crop_image -i "${file_mt1}.nii.gz" -m "mask_${file_mt1}.nii.gz" -o "${file_mt1}_crop.nii.gz"
-sct_crop_image -i "${file_mt1_seg}.nii.gz" -m "mask_${file_mt1}.nii.gz" -o "${file_mt1}_crop_seg.nii.gz"
-file_mt1="${file_mt1}_crop"
+sct_crop_image -i "${file_mt1}".nii.gz -m "mask_${file_mt1}".nii.gz -o "${file_mt1}"_crop.nii.gz
+sct_crop_image -i "${file_mt1_seg}".nii.gz -m "mask_${file_mt1}".nii.gz -o "${file_mt1}"_crop_seg.nii.gz
+file_mt1="${file_mt1}"_crop
 # Register mt0->mt1
 # Tips: here we only use rigid transformation because both images have very
 # similar sequence parameters. We don't want to use SyN/BSplineSyN to avoid
 # introducing spurious deformations.
-sct_register_multimodal -i "${file_mt0}.nii.gz" \
-                        -d "${file_mt1}.nii.gz" \
-                        -dseg "${file_mt1}_seg.nii.gz" \
+sct_register_multimodal -i "${file_mt0}".nii.gz \
+                        -d "${file_mt1}".nii.gz \
+                        -dseg "${file_mt1}"_seg.nii.gz \
                         -param step=1,type=im,algo=rigid,slicewise=1,metric=CC \
                         -x spline \
                         -qc "${PATH_QC}"
@@ -156,21 +156,21 @@ sct_register_multimodal -i "${file_mt0}.nii.gz" \
 # Tips: First step: slicereg based on images, with large smoothing to capture
 # potential motion between anat and mt, then at second step: bpslinesyn in order to
 # adapt the shape of the cord to the mt modality (in case there are distortions between anat and mt).
-sct_register_multimodal -i "${SCT_DIR}/data/PAM50/template/PAM50_t2.nii.gz" \
-                        -iseg "${SCT_DIR}/data/PAM50/template/PAM50_cord.nii.gz" \
-                        -d "${file_mt1}.nii.gz" \
-                        -dseg "${file_mt1}_seg.nii.gz" \
+sct_register_multimodal -i "${SCT_DIR}"/data/PAM50/template/PAM50_t2.nii.gz \
+                        -iseg "${SCT_DIR}"/data/PAM50/template/PAM50_cord.nii.gz \
+                        -d "${file_mt1}".nii.gz \
+                        -dseg "${file_mt1}"_seg.nii.gz \
                         -param step=1,type=seg,algo=centermass:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 \
                         -initwarp warp_template2anat.nii.gz \
                         -initwarpinv warp_anat2template.nii.gz \
                         -qc "${PATH_QC}"
 # Rename warping fields for clarity
-mv "warp_PAM50_t22${file_mt1}.nii.gz" warp_template2mt.nii.gz
-mv "warp_${file_mt1}2PAM50_t2.nii.gz" warp_mt2template.nii.gz
+mv warp_PAM50_t22"${file_mt1}".nii.gz warp_template2mt.nii.gz
+mv warp_"${file_mt1}"2PAM50_t2.nii.gz warp_mt2template.nii.gz
 # Warp template
-sct_warp_template -d "${file_mt1}.nii.gz" -w warp_template2mt.nii.gz -ofolder label_MT -qc "${PATH_QC}"
+sct_warp_template -d "${file_mt1}".nii.gz -w warp_template2mt.nii.gz -ofolder label_MT -qc "${PATH_QC}"
 # Compute mtr
-sct_compute_mtr -mt0 "${file_mt0}_reg.nii.gz" -mt1 "${file_mt1}.nii.gz"
+sct_compute_mtr -mt0 "${file_mt0}"_reg.nii.gz -mt1 "${file_mt1}".nii.gz
 # compute MTR in dorsal columns between levels C2 and C5 (append across subjects)
 sct_extract_metric -i mtr.nii.gz -f label_MT/atlas -l 53 -vert 2:5 -vertfile label_MT/template/PAM50_levels.nii.gz \
                    -method map -o "${PATH_RESULTS}/MTR_in_DC.csv" -append 1
@@ -178,8 +178,8 @@ sct_extract_metric -i mtr.nii.gz -f label_MT/atlas -l 53 -vert 2:5 -vertfile lab
 # Verify presence of output files and write log file if error
 # ======================================================================================================================
 FILES_TO_CHECK=(
-  "$file_t2_seg.nii.gz"
-  "mtr.nii.gz"
+  "${file_t2_seg}".nii.gz
+  mtr.nii.gz
 )
 for file in "${FILES_TO_CHECK[@]}"; do
   if [ ! -e "${file}" ]; then
@@ -188,11 +188,11 @@ for file in "${FILES_TO_CHECK[@]}"; do
 done
 
 # Display useful info for the log
-end=`date +%s`
-runtime=$((end-start))
+end="$(date +%s)"
+runtime="$((end-start))"
 echo
 echo "~~~"
-echo "SCT version: `sct_version`"
-echo "Ran on:      `uname -nsr`"
-echo "Duration:    $(($runtime / 3600))hrs $((($runtime / 60) % 60))min $(($runtime % 60))sec"
+echo "SCT version: $(sct_version)"
+echo "Ran on:      $(uname -nsr)"
+echo "Duration:    $((runtime / 3600))hrs $(( (runtime / 60) % 60))min $((runtime % 60))sec"
 echo "~~~"
diff --git a/single_subject/batch_single_subject.sh b/single_subject/batch_single_subject.sh
index f98eeee..c9ebff6 100755
--- a/single_subject/batch_single_subject.sh
+++ b/single_subject/batch_single_subject.sh
@@ -23,7 +23,7 @@ echo -e "\nStarted at: $(date +%x_%r)"
 # Source: https://unix.stackexchange.com/a/497540
 if ! command -v fsleyes > /dev/null; then
   fsleyes() {
-    printf 'WARNING: FSLeyes is not installed, so the following command was skipped:\nfsleyes %s\n' "$*";
+    printf 'WARNING: FSLeyes is not installed, so the following command was skipped:\nfsleyes %s\n' "${*@Q}";
   };
 fi
 
@@ -136,7 +136,7 @@ sct_create_mask -i mt1.nii.gz -p centerline,mt1_seg.nii.gz -size 35mm -f cylinde
 
 # Register template->mt1. The flag -initwarp ../t2/warp_template2anat.nii.gz initializes the registration using the
 # template->t2 transformation which was previously estimated
-sct_register_multimodal -i $SCT_DIR/data/PAM50/template/PAM50_t2.nii.gz -iseg $SCT_DIR/data/PAM50/template/PAM50_cord.nii.gz -d mt1.nii.gz -dseg mt1_seg.nii.gz -m mask_mt1.nii.gz -initwarp ../t2/warp_template2anat.nii.gz -param step=1,type=seg,algo=centermass:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -owarp warp_template2mt.nii.gz -qc ~/qc_singleSubj
+sct_register_multimodal -i "${SCT_DIR}"/data/PAM50/template/PAM50_t2.nii.gz -iseg "${SCT_DIR}"/data/PAM50/template/PAM50_cord.nii.gz -d mt1.nii.gz -dseg mt1_seg.nii.gz -m mask_mt1.nii.gz -initwarp ../t2/warp_template2anat.nii.gz -param step=1,type=seg,algo=centermass:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -owarp warp_template2mt.nii.gz -qc ~/qc_singleSubj
 # Tips: Here we only use the segmentations (type=seg) to minimize the sensitivity of the registration procedure to
 #       image artifacts.
 # Tips: Step 1: algo=centermass to align source and destination segmentations, then Step 2: algo=bpslinesyn to adapt the
@@ -228,13 +228,13 @@ sct_extract_metric -i t2s.nii.gz -f t2s_gmseg.nii.gz -method bin -z 2:12 -o t2s_
 
 # Register template->t2s (using warping field generated from template<->t2 registration)
 # Tips: Here we use the WM seg for the iseg/dseg fields in order to account for both the cord and the GM shape.
-sct_register_multimodal -i "${SCT_DIR}/data/PAM50/template/PAM50_t2s.nii.gz" -iseg "${SCT_DIR}/data/PAM50/template/PAM50_wm.nii.gz" -d t2s.nii.gz -dseg t2s_wmseg.nii.gz -initwarp ../t2/warp_template2anat.nii.gz -initwarpinv ../t2/warp_anat2template.nii.gz -owarp warp_template2t2s.nii.gz -owarpinv warp_t2s2template.nii.gz -param step=1,type=seg,algo=rigid:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -qc ~/qc_singleSubj
+sct_register_multimodal -i "${SCT_DIR}"/data/PAM50/template/PAM50_t2s.nii.gz -iseg "${SCT_DIR}"/data/PAM50/template/PAM50_wm.nii.gz -d t2s.nii.gz -dseg t2s_wmseg.nii.gz -initwarp ../t2/warp_template2anat.nii.gz -initwarpinv ../t2/warp_anat2template.nii.gz -owarp warp_template2t2s.nii.gz -owarpinv warp_t2s2template.nii.gz -param step=1,type=seg,algo=rigid:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -qc ~/qc_singleSubj
 # Warp template
 sct_warp_template -d t2s.nii.gz -w warp_template2t2s.nii.gz -qc ~/qc_singleSubj
 
 cd ../mt
 # Register template->mt via t2s to account for GM segmentation
-sct_register_multimodal -i "${SCT_DIR}/data/PAM50/template/PAM50_t2.nii.gz" -iseg "${SCT_DIR}/data/PAM50/template/PAM50_cord.nii.gz" -d mt1.nii.gz -dseg mt1_seg.nii.gz -param step=1,type=seg,algo=centermass:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -m mask_mt1.nii.gz -initwarp ../t2s/warp_template2t2s.nii.gz -owarp warp_template2mt.nii.gz -qc ~/qc_singleSubj
+sct_register_multimodal -i "${SCT_DIR}"/data/PAM50/template/PAM50_t2.nii.gz -iseg "${SCT_DIR}"/data/PAM50/template/PAM50_cord.nii.gz -d mt1.nii.gz -dseg mt1_seg.nii.gz -param step=1,type=seg,algo=centermass:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -m mask_mt1.nii.gz -initwarp ../t2s/warp_template2t2s.nii.gz -owarp warp_template2mt.nii.gz -qc ~/qc_singleSubj
 # Warp template
 sct_warp_template -d mt1.nii.gz -w warp_template2mt.nii.gz -qc ~/qc_singleSubj
 # Check results
@@ -279,7 +279,7 @@ sct_deepseg_sc -i dmri_moco_dwi_mean.nii.gz -c dwi -qc ~/qc_singleSubj
 #       -param, so it will not make a difference here)
 # Note: the flag “-initwarpinv" provides a transformation dmri->template, in case you would like to bring all your DTI
 #       metrics in the PAM50 space (e.g. group averaging of FA maps)
-sct_register_multimodal -i "${SCT_DIR}/data/PAM50/template/PAM50_t1.nii.gz" -iseg "${SCT_DIR}/data/PAM50/template/PAM50_cord.nii.gz" -d dmri_moco_dwi_mean.nii.gz -dseg dmri_moco_dwi_mean_seg.nii.gz -initwarp ../t2s/warp_template2t2s.nii.gz -initwarpinv ../t2s/warp_t2s2template.nii.gz -owarp warp_template2dmri.nii.gz -owarpinv warp_dmri2template.nii.gz -param step=1,type=seg,algo=centermass:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -qc ~/qc_singleSubj
+sct_register_multimodal -i "${SCT_DIR}"/data/PAM50/template/PAM50_t1.nii.gz -iseg "${SCT_DIR}"/data/PAM50/template/PAM50_cord.nii.gz -d dmri_moco_dwi_mean.nii.gz -dseg dmri_moco_dwi_mean_seg.nii.gz -initwarp ../t2s/warp_template2t2s.nii.gz -initwarpinv ../t2s/warp_t2s2template.nii.gz -owarp warp_template2dmri.nii.gz -owarpinv warp_dmri2template.nii.gz -param step=1,type=seg,algo=centermass:step=2,type=seg,algo=bsplinesyn,slicewise=1,iter=3 -qc ~/qc_singleSubj
 # Warp template (so 'label/atlas' can be used to extract metrics)
 sct_warp_template -d dmri_moco_dwi_mean.nii.gz -w warp_template2dmri.nii.gz -qc ~/qc_singleSubj
 # Check results in the QC report
@@ -313,7 +313,7 @@ sct_fmri_moco -i fmri.nii.gz -m mask_fmri.nii.gz -qc ~/qc_singleSubj -qc-seg t2_
 #       ANTs_SyN superpower to find a suitable transformation between the PAM50_t2s and the fMRI scan. We don't want to
 #       put too many iterations because this registration is very sensitive to the artifacts (drop out) in the image.
 #       Also, we want a 3D transformation (not 2D) because we need the through-z regularization.
-sct_register_multimodal -i "${SCT_DIR}/data/PAM50/template/PAM50_t2s.nii.gz" -d fmri_moco_mean.nii.gz -dseg t2_seg_reg.nii.gz -param step=1,type=im,algo=syn,metric=CC,iter=5,slicewise=0 -initwarp ../t2s/warp_template2t2s.nii.gz -initwarpinv ../t2s/warp_t2s2template.nii.gz -owarp warp_template2fmri.nii.gz -owarpinv warp_fmri2template.nii.gz -qc ~/qc_singleSubj
+sct_register_multimodal -i "${SCT_DIR}"/data/PAM50/template/PAM50_t2s.nii.gz -d fmri_moco_mean.nii.gz -dseg t2_seg_reg.nii.gz -param step=1,type=im,algo=syn,metric=CC,iter=5,slicewise=0 -initwarp ../t2s/warp_template2t2s.nii.gz -initwarpinv ../t2s/warp_t2s2template.nii.gz -owarp warp_template2fmri.nii.gz -owarpinv warp_fmri2template.nii.gz -qc ~/qc_singleSubj
 # Check results in the QC report
 
 # Warp template with the spinal levels (-s 1)