Data Analysis and Visualization for High-Resolution Hippocampal Perfusion
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Hippocampal perfusion
This repository contains the data analysis code and (visualization) notebooks related to the preprint:
"Novel insights into hippocampal perfusion using high-resolution, multi-modal 7T MRI"
Code Snippets
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | run: import numpy as np import nibabel as nib LR = nib.load(input[0]) LR_labels = LR.get_fdata() LR_relabeled = np.zeros(LR_labels.shape) relabeling = [[1, 1],[2, 2],[20, 3], [21, 4],[22, 5],[23, 6]] for labels in relabeling: LR_relabeled[LR_labels==labels[0]] = labels[1] img = nib.Nifti1Image(LR_relabeled.astype(np.int8), header=LR.header, affine=LR.affine) nib.save(img, output[0]) |
37 38 39 | shell: 'reg_aladin -flo {input.flo} -ref {input.ref} -res {output.warped} -aff {output.xfm_ras} -rigOnly -nac && ' 'c3d_affine_tool {output.xfm_ras} -oitk {output.xfm_itk}' |
53 54 55 | shell: 'ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS={threads} ' 'antsApplyTransforms -d 3 --interpolation NearestNeighbor -i {input.nii} -o {output} -r {input.ref} -t {input.xfm}' |
66 67 | shell: "c3d {input} -split -foreach -smooth 0.3mm -endfor -merge -o {output}" |
9 10 | shell: "fslmaths {input} -bin {output}" |
29 30 | shell: "{params.merge_cmd}" |
40 41 42 43 | shell: "wb_command -metric-reduce {input} MEAN {output.avg} -only-numeric &&" "wb_command -metric-reduce {input} STDEV {output.std} -only-numeric &&" "wb_command -metric-reduce {input} COV {output.cov} -only-numeric " |
54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 | run: import numpy as np import nibabel as nib from scipy.stats import variation metric = nib.load(input[0]) data = np.zeros((len(metric.darrays[0].data),len(input))) gii_merged = nib.gifti.GiftiImage() for i,in_metric in enumerate(input): data[:,i] = nib.load(in_metric).darrays[0].data gii_merged.add_gifti_data_array( nib.gifti.GiftiDataArray(data=data[:,i].astype(np.float32) ) ) nib.save(gii_merged, output.merged) shell("wb_command -set-structure {output.merged} CORTEX_RIGHT") metric.darrays[0].data = np.nanmean(data,1) nib.save(metric, output.avg) metric.darrays[0].data = np.nanstd(data,1) nib.save(metric, output.std) metric.darrays[0].data = np.nanstd(data,1)/np.nanmean(data,1) nib.save(metric, output.cov) |
103 104 | shell: "wb_command -metric-gradient {input.midthickness} {input.metric} {output} -presmooth {params.sigma} -average-normals" |
7 | shell: "mris_convert {input} {output}" |
15 | shell: "mri_convert {input} {output}" |
23 | shell: 'mri_info {input} --tkr2scanner > {output}' |
33 | shell: 'wb_command -surface-apply-affine {input.surf} {input.tkr2scanner} {output}' |
46 | shell: 'wb_command -surface-resample {input.surf} {input.current_sphere} {input.new_sphere} {params.method} {output}' |
56 | shell: 'wb_command -surface-cortex-layer {input.white} {input.pial} 0.5 {output}' |
66 67 | shell: "wb_command -surface-generate-inflated {input} {output.inflated} {output.very_inflated} -iterations-scale 0.75" |
82 83 84 85 | shell: """ wb_command -label-resample {input.label} {input.current_sphere} {input.new_sphere} {params.method} {output} -area-surfs {input.current_surf} {input.new_surf} """ |
98 99 100 | shell: 'wb_command -label-to-volume-mapping {input.label} {input.surf} {input.vol_ref} {output}' ' -ribbon-constrained {input.white_surf} {input.pial_surf} -greedy' |
7 8 | shell: "wb_command -surface-vertex-areas {input} {output}" |
15 16 | shell: "wb_command -surface-vertex-areas {input} {output}" |
25 26 27 28 | shell: """ wb_command -metric-math x/y {output} -var x {input.native} -var y {input.unfolded} """ |
39 40 | shell: "wb_command -surface-smoothing {input} {params.strength} {params.iterations} {output}" |
47 48 | shell: "wb_command -surface-curvature {input} -mean {output}" |
58 59 | shell: "wb_command -surface-to-surface-3d-distance {input.outer} {input.inner} {output}" |
72 73 74 75 | shell: "wb_command -surface-to-surface-3d-distance {input.avg} {input.subject} {output.distance} -vectors {output.displacement} && " "wb_command -metric-math 'metric' {output.distance} -fixnan 0 -var metric {output.distance} && " "wb_command -metric-math 'metric' {output.displacement} -fixnan 0 -var metric {output.displacement}" |
95 96 97 98 99 100 101 | shell: """ jupyter nbconvert \ --TagRemovePreprocessor.enabled=True \ --TagRemovePreprocessor.remove_cell_tags snakemake-job-properties \ --to html {input} """ |
14 15 | shell: "bash ./{params.script} {wildcards.subject} {input.gradcorrect} {params.mp2rage_correction}" |
29 30 | shell: "bash ./{params.script} -i {input.inv2} -u {input.t1w} -o `dirname {output}`" |
44 45 | shell: "bash {params.script} -i {input}" |
56 57 | shell: "cp {input.nii} {output.nii} && cp {input.json} {output.json}" |
70 71 72 73 74 75 76 77 78 79 80 81 82 | shell: "bash scripts/skullstripping/skullstrip.sh {params.script} {input} `realpath {output}` " #&> {log} {params.out_dir} # Apply the brain mask rule apply_brain_mask: input: t1w = rules.mprageise.output, brain_mask = rules.skull_stripping.output output: 'results/freesurfer/sub-{subject}/mri/orig/001.mgz' group: 'preprocessing' singularity: config['singularity_freesurfer'] shell: "mri_mask {input.t1w} {input.brain_mask} {output}" |
101 102 103 | shell: "export SUBJECTS_DIR={params.sd} && " "recon-all -all -s sub-{wildcards.subject} -no-wsgcaatlas -notal-check -threads 8" |
116 117 | shell: "c3d_affine_tool -ref {input.ref} -src {input.src} {input.xfm} -fsl2ras -oitk {output}" |
134 135 136 | shell: "ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS={threads} " "antsApplyTransforms -d 3 --interpolation Linear -i {input.nii} -o {output} -r {input.ref} -t {input.xfm2crop} -t {input.xfm2ref} -t {input.xfm2tse}" |
144 145 | shell: "c3d {input} -flip x -o {output}" |
161 162 | shell: "wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} -ribbon-constrained {input.outer} {input.inner} -volume-roi {input.ribbon}" |
174 175 | shell: "wb_command -metric-math '(t1w/t2w)' {output} -var t1w {input.t1w} -var t2w {input.t2w} -fixnan 0" |
13 14 | shell: "c3d_affine_tool -ref {input.ref} -src {input.src} {input.xfm} -fsl2ras -oitk {output}" |
27 28 29 30 31 32 | shell: """ ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS={threads} antsApplyTransforms -d 3 --interpolation Linear -i {input.nii} -o {output} -r {input.ref} \ -t {input.xfm2crop} -t {input.xfm2ref} -t {input.xfm2tse} """ |
39 40 | shell: "c3d {input} -flip x -o {output}" |
52 53 54 55 56 57 58 59 60 61 | shell: """ if [ {wildcards.tpl_res} = 'hires' ] ; then wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} \ -ribbon-constrained {input.outer} {input.inner} -volume-roi {input.ribbon} else wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} \ -trilinear fi """ |
68 69 | shell: "AverageImages 3 {output} 0 {input}" |
82 83 84 85 86 87 | shell: """ ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS={threads} antsApplyTransforms -d 3 --interpolation Linear -i {input.nii} -o {output} -r {input.ref} \ -t {input.xfm2crop} -t {input.xfm2ref} -t {input.xfm2tse} """ |
94 95 | shell: "c3d {input} -flip x -o {output}" |
107 108 109 110 111 112 113 114 115 116 | shell: """ if [ {wildcards.tpl_res} = 'hires' ] ; then wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} \ -ribbon-constrained {input.outer} {input.inner} -volume-roi {input.ribbon} else wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} \ -trilinear fi """ |
126 127 | shell: "fslsplit {input} {params.prefix} -t" |
139 140 141 142 143 144 145 146 147 148 | shell: """ hemi={wildcards.hemi} in_dir=`dirname {input.nii}` out_dir=`dirname {output}` for file in $in_dir/*.nii.gz ; do out_file=`basename $file` antsApplyTransforms -d 3 --interpolation Linear -i $file -o $out_dir/$out_file -r {input.ref} -t {input.xfm2crop} -t {input.xfm2ref} -t {input.xfm2tse} done """ |
155 156 157 158 159 160 161 162 163 | shell: """ in_dir=`dirname {input}` out_dir=`dirname {output}` for file in $in_dir/*.nii.gz ; do out_file=`basename $file` c4d $file -flip x -o $out_dir/$out_file done """ |
175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 | shell: """ in_dir=`dirname {input.nii}` out_dir=`dirname {output}` exclude="0098 0197 0296 0395 0494 0593 0692 0791" for file in $in_dir/*.nii.gz ; do fname=`basename $file .nii.gz` vol=${{fname:10:4}} if [[ $exclude != *$vol* ]] ; then out_file=${{fname}}.shape.gii wb_command -volume-to-surface-mapping $file {input.midthickness} $out_dir/$out_file -trilinear fi done """ |
200 201 | shell: "{params.merge_cmd}" |
212 213 214 215 216 | shell: """ ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS={threads} antsApplyTransforms -d 3 --interpolation Linear -i {input.nii} -o {output} -r {input.nii} -t {input.xfm} """ |
227 228 229 230 | shell: """ wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} -trilinear """ |
9 10 | shell: "mri_convert {input.t1w} {output} -nc -rl {input.fs}" |
23 24 | shell: "reg_aladin -flo {input.src} -ref {input.ref} -aff {output.xfm} -rigOnly -nac" |
36 37 | shell: "c3d_affine_tool {input.xfm} -oitk {output}" |
55 56 57 | shell: "ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS={threads} " "antsApplyTransforms -d 3 --interpolation Linear -i {input.nii} -o {output} -r {input.ref} -t {input.xfm2crop} -t {input.xfm2ref} -t {input.xfm2tse} -t {input.xfm2hires}" |
65 66 | shell: "c3d {input} -flip x -o {output}" |
82 83 | shell: "wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} -ribbon-constrained {input.outer} {input.inner} -volume-roi {input.ribbon}" |
14 15 16 | shell: "ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS={threads} " "antsApplyTransforms -d 3 --interpolation Linear -i {input.nii} -o {output} -r {input.ref} -t {input.xfm} -t {input.init}" |
24 25 | shell: "c3d {input} -flip x -o {output}" |
41 42 | shell: "wb_command -volume-to-surface-mapping {input.nii} {input.midthickness} {output} -ribbon-constrained {input.outer} {input.inner} -volume-roi {input.ribbon}" |
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Created: 1yr ago
Updated: 1yr ago
Maitainers:
public
URL:
https://github.com/royhaast/hippocampal_perfusion
Name:
hippocampal_perfusion
Version:
1
Downloaded:
0
Copyright:
Public Domain
License:
None
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