batch_single_subject.sh: Turn multi-line commands into one-liners

joshuacwnewton · joshuacwnewton · commit 67355b772eb8 · 2021-11-07T13:07:06.000-05:00
diff --git a/single_subject/batch_single_subject.sh b/single_subject/batch_single_subject.sh
@@ -69,8 +69,7 @@ sct_label_vertebrae -i t2.nii.gz -s t2_seg.nii.gz -c t2 -qc ~/qc_singleSubj
 #       inter-vertebral disc level. The convention is: Value 3 —> C2-C3 disc, Value 4 —> C3-C4 disc, etc.
 
 # OPTIONAL: If automatic labeling did not work, you can initialize with manual identification of C2-C3 disc:
-#sct_label_utils -i t2.nii.gz -create-viewer 3 -o label_c2c3.nii.gz \
-#                -msg "Click at the posterior tip of C2/C3 inter-vertebral disc"
+#sct_label_utils -i t2.nii.gz -create-viewer 3 -o label_c2c3.nii.gz -msg "Click at the posterior tip of C2/C3 inter-vertebral disc"
 #sct_label_vertebrae -i t2.nii.gz -s t2_seg.nii.gz -c t2 -initlabel label_c2c3.nii.gz -qc ~/qc_singleSubj
 
 # Create labels at C3 and T2 mid-vertebral levels. These labels are needed for template registration.
@@ -79,8 +78,7 @@ sct_label_utils -i t2_seg_labeled.nii.gz -vert-body 3,9 -o t2_labels_vert.nii.gz
 # OPTIONAL: You might want to completely bypass sct_label_vertebrae and do the labeling manually. In that case, we
 # provide a viewer to do so conveniently. In the example command below, we will create labels at the inter-vertebral
 # discs C2-C3 (value=3), C3-C4 (value=4) and C4-C5 (value=5).
-#sct_label_utils -i t2.nii.gz -create-viewer 3,4,5 -o labels_disc.nii.gz \
-#                -msg "Place labels at the posterior tip of each inter-vertebral disc. E.g. Label 3: C2/C3, Label 4: C3/C4, etc."
+#sct_label_utils -i t2.nii.gz -create-viewer 3,4,5 -o labels_disc.nii.gz -msg "Place labels at the posterior tip of each inter-vertebral disc. E.g. Label 3: C2/C3, Label 4: C3/C4, etc."
 
 
 
@@ -99,10 +97,7 @@ sct_warp_template -d t2.nii.gz -w warp_template2anat.nii.gz -a 0 -qc ~/qc_single
 #       info_label.txt lists all template files.
 
 # Check results using Fsleyes. Tips: use the right arrow key to switch overlay on/off.
-fsleyes t2.nii.gz -cm greyscale -a 100.0 \
-        label/template/PAM50_t2.nii.gz -cm greyscale -dr 0 4000 -a 100.0 \
-        label/template/PAM50_gm.nii.gz -cm red-yellow -dr 0.4 1 -a 50.0 \
-        label/template/PAM50_wm.nii.gz -cm blue-lightblue -dr 0.4 1 -a 50.0 &
+fsleyes t2.nii.gz -cm greyscale -a 100.0 label/template/PAM50_t2.nii.gz -cm greyscale -dr 0 4000 -a 100.0 label/template/PAM50_gm.nii.gz -cm red-yellow -dr 0.4 1 -a 50.0 label/template/PAM50_wm.nii.gz -cm blue-lightblue -dr 0.4 1 -a 50.0 &
 
 
 
@@ -132,15 +127,7 @@ 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
@@ -155,10 +142,7 @@ sct_register_multimodal -i $SCT_DIR/data/PAM50/template/PAM50_t2.nii.gz \
 # Warp template
 sct_warp_template -d mt1.nii.gz -w warp_template2mt.nii.gz -a 1 -qc ~/qc_singleSubj
 # Check results using Fsleyes. Tips: use the right arrow key to switch overlay on/off.
-fsleyes mt1.nii.gz -cm greyscale -a 100.0 \
-        label/template/PAM50_t2.nii.gz -cm greyscale -dr 0 4000 -a 100.0 \
-        label/template/PAM50_gm.nii.gz -cm red-yellow -dr 0.4 1 -a 50.0 \
-        label/template/PAM50_wm.nii.gz -cm blue-lightblue -dr 0.4 1 -a 50.0 &
+fsleyes mt1.nii.gz -cm greyscale -a 100.0 label/template/PAM50_t2.nii.gz -cm greyscale -dr 0 4000 -a 100.0 label/template/PAM50_gm.nii.gz -cm red-yellow -dr 0.4 1 -a 50.0 label/template/PAM50_wm.nii.gz -cm blue-lightblue -dr 0.4 1 -a 50.0 &
 
 
 
@@ -167,8 +151,7 @@ fsleyes mt1.nii.gz -cm greyscale -a 100.0 \
 
 # Register mt0->mt1 using z-regularized slicewise translations (algo=slicereg)
 # Note: Segmentation and mask can be re-used from "MT registration" section
-sct_register_multimodal -i mt0.nii.gz -d mt1.nii.gz -dseg mt1_seg.nii.gz -m mask_mt1.nii.gz \
-                        -param step=1,type=im,algo=slicereg,metric=CC -x spline -qc ~/qc_singleSubj
+sct_register_multimodal -i mt0.nii.gz -d mt1.nii.gz -dseg mt1_seg.nii.gz -m mask_mt1.nii.gz -param step=1,type=im,algo=slicereg,metric=CC -x spline -qc ~/qc_singleSubj
 # Check results using Fsleyes. Tips: use the right arrow key to switch overlay on/off.
 fsleyes mt1.nii.gz mt0_reg.nii.gz &
 # Compute MTR
@@ -215,28 +198,11 @@ 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
 
 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
 
 
 
@@ -246,10 +212,7 @@ sct_register_multimodal -i "${SCT_DIR}/data/PAM50/template/PAM50_t2.nii.gz" \
 # In order to use the PAM50 atlas to extract/aggregate image data, the atlas must first be transformed to the MT space
 sct_warp_template -d mt1.nii.gz -w warp_template2mt.nii.gz -a 1 -qc ~/qc_singleSubj
 # Check results
-fsleyes mt1.nii.gz -cm greyscale -a 100.0 \
-        label/template/PAM50_t2.nii.gz -cm greyscale -dr 0 4000 -a 100.0 \
-        label/template/PAM50_gm.nii.gz -cm red-yellow -dr 0.4 1 -a 100.0 \
-        label/template/PAM50_wm.nii.gz -cm blue-lightblue -dr 0.4 1 -a 100.0 &
+fsleyes mt1.nii.gz -cm greyscale -a 100.0 label/template/PAM50_t2.nii.gz -cm greyscale -dr 0 4000 -a 100.0 label/template/PAM50_gm.nii.gz -cm red-yellow -dr 0.4 1 -a 100.0 label/template/PAM50_wm.nii.gz -cm blue-lightblue -dr 0.4 1 -a 100.0 &
 
 # Extract MTR for each slice within the white matter (combined label: #51)
 # Tips: To list all available labels, type: "sct_extract_metric"
@@ -259,9 +222,7 @@ sct_extract_metric -i mtr.nii.gz -f label/atlas -method map -l 51 -o mtr_in_wm.c
 sct_extract_metric -i mtr.nii.gz -f label/atlas -method map -l 4,5 -z 5:15 -o mtr_in_cst.csv
 # You can specify the vertebral levels to extract MTR from. For example, to quantify MTR between C2 and C4 levels in the
 # dorsal column (combined label: #53) using weighted average:
-sct_extract_metric -i mtr.nii.gz -f label/atlas -method map -l 53 \
-                   -vert 2:4 -vertfile label/template/PAM50_levels.nii.gz \
-                   -o mtr_in_dc.csv
+sct_extract_metric -i mtr.nii.gz -f label/atlas -method map -l 53 -vert 2:4 -vertfile label/template/PAM50_levels.nii.gz -o mtr_in_dc.csv
 
 
 # Diffusion-weighted MRI
@@ -278,8 +239,7 @@ sct_deepseg_sc -i dmri_mean.nii.gz -c dwi -qc ~/qc_singleSubj
 sct_create_mask -i dmri_mean.nii.gz -p centerline,dmri_mean_seg.nii.gz -f cylinder -size 35mm
 
 # Motion correction (moco)
-sct_dmri_moco -i dmri.nii.gz -m mask_dmri_mean.nii.gz -bvec bvecs.txt \
-              -qc ~/qc_singleSubj -qc-seg dmri_mean_seg.nii.gz
+sct_dmri_moco -i dmri.nii.gz -m mask_dmri_mean.nii.gz -bvec bvecs.txt -qc ~/qc_singleSubj -qc-seg dmri_mean_seg.nii.gz
 
 # Segment SC on motion-corrected mean dwi data (check results in the QC report)
 sct_deepseg_sc -i dmri_moco_dwi_mean.nii.gz -c dwi -qc ~/qc_singleSubj
@@ -289,16 +249,7 @@ 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
@@ -308,10 +259,7 @@ sct_dmri_compute_dti -i dmri_moco.nii.gz -bval bvals.txt -bvec bvecs.txt
 # Tips: the flag "-method restore" estimates the tensor with robust fit (RESTORE method [2])
 
 # Compute FA within the white matter from individual level 2 to 5
-sct_extract_metric -i dti_FA.nii.gz -f label/atlas \
-                   -l 51 -method map \
-                   -vert 2:5 -vertfile label/template/PAM50_levels.nii.gz -perlevel 1 \
-                   -o fa_in_wm.csv
+sct_extract_metric -i dti_FA.nii.gz -f label/atlas -l 51 -method map -vert 2:5 -vertfile label/template/PAM50_levels.nii.gz -perlevel 1 -o fa_in_wm.csv
 
 
 
@@ -328,33 +276,20 @@ sct_register_multimodal -i ../t2/t2_seg.nii.gz -d fmri_mean.nii.gz -identity 1
 sct_create_mask -i fmri.nii.gz -p centerline,t2_seg_reg.nii.gz -size 35mm -f cylinder
 
 # Motion correction (using mask)
-sct_fmri_moco -i fmri.nii.gz -m mask_fmri.nii.gz \
-              -qc ~/qc_singleSubj -qc-seg t2_seg_reg.nii.gz
+sct_fmri_moco -i fmri.nii.gz -m mask_fmri.nii.gz -qc ~/qc_singleSubj -qc-seg t2_seg_reg.nii.gz
 
 # Register the template to the fMRI scan.
 # Note: here we don't rely on the segmentation because it is difficult to obtain one automatically. Instead, we rely on
 #       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)
 sct_warp_template -d fmri_moco_mean.nii.gz -w warp_template2fmri.nii.gz -s 1 -a 0 -qc ~/qc_singleSubj
 # Check results
-fsleyes --scene lightbox --hideCursor fmri_moco_mean.nii.gz -cm greyscale -dr 0 1000 \
-                                      label/spinal_levels/spinal_level_03 -cm red \
-                                      label/spinal_levels/spinal_level_04 -cm blue \
-                                      label/spinal_levels/spinal_level_05 -cm green \
-                                      label/spinal_levels/spinal_level_06 -cm yellow
+fsleyes --scene lightbox --hideCursor fmri_moco_mean.nii.gz -cm greyscale -dr 0 1000 label/spinal_levels/spinal_level_03 -cm red label/spinal_levels/spinal_level_04 -cm blue label/spinal_levels/spinal_level_05 -cm green label/spinal_levels/spinal_level_06 -cm yellow
 
 
 
