Skip to content

Commit

Permalink
initial nf-neuro commit (following nf-scil:PR#169)
Browse files Browse the repository at this point in the history
  • Loading branch information
@anroy1
anroy1 committed Sep 24, 2024
1 parent 8efec79 commit eee93dc
Show file tree
Hide file tree
Showing 3 changed files with 146 additions and 15 deletions.
48 changes: 36 additions & 12 deletions subworkflows/nf-neuro/preproc_t1/main.nf
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,18 +3,22 @@ include { DENOISING_NLMEANS } from '../../../modules/nf-neuro/denoising/nlmeans/
include { PREPROC_N4 } from '../../../modules/nf-neuro/preproc/n4/main'
include { IMAGE_RESAMPLE } from '../../../modules/nf-neuro/image/resample/main'
include { BETCROP_ANTSBET } from '../../../modules/nf-neuro/betcrop/antsbet/main'
include { BETCROP_SYNTHBET} from '../../../modules/nf-neuro/betcrop/synthbet/main'
include { BETCROP_CROPVOLUME as BETCROP_CROPVOLUME_T1 } from '../../../modules/nf-neuro/betcrop/cropvolume/main'
include { BETCROP_CROPVOLUME as BETCROP_CROPVOLUME_MASK } from '../../../modules/nf-neuro/betcrop/cropvolume/main'

params.run_synthbet = params.run_synthbet ?: false

workflow PREPROC_T1 {

take:
ch_image // channel: [ val(meta), [ image ] ]
ch_template // channel: [ val(meta), [ template ] ]
ch_probability_map // channel: [ val(meta), [ probability_map ] ]
ch_template // channel: [ val(meta), [ template ] ] , optional
ch_probability_map // channel: [ val(meta), [ probability_map ] ] , optional
ch_mask_nlmeans // channel: [ val(meta), [ mask ] ] , optional
ch_ref_n4 // channel: [ val(meta), [ ref, ref_mask ] ] , optional
ch_ref_resample // channel: [ val(meta), [ ref ] ] , optional
ch_weights // channel: [ val(meta), [ weights ] ] , optional

main:

Expand All @@ -36,28 +40,48 @@ workflow PREPROC_T1 {
ch_versions = ch_versions.mix(IMAGE_RESAMPLE.out.versions.first())

// ** Brain extraction ** //
ch_bet = IMAGE_RESAMPLE.out.image.join(ch_template).join(ch_probability_map)
if ( params.run_synthbet) {
BETCROP_ANTSBET ( ch_bet )
ch_bet = IMAGE_RESAMPLE.out.image.join(ch_weights)
ch_versions = ch_versions.mix(BETCROP_ANTSBET.out.versions.first())
BETCROP_SYNTHBET ( ch_bet )
ch_versions = ch_versions.mix(BETCROP_SYNTHBET.out.versions.first())

// ** Setting BET output ** //
image_bet = BETCROP_SYNTHBET.out.bet_image
mask_bet = BETCROP_SYNTHBET.out.brain_mask
}

else {
ch_template = ch_template.ifEmpty(Channel.error('Template is required for ANTS registration'))
ch_probability_map = ch_probability_map.ifEmpty(Channel.error('Probability map is required for ANTS registration'))
ch_bet = IMAGE_RESAMPLE.out.image.join(ch_template).join(ch_probability_map)
BETCROP_ANTSBET ( ch_bet )
ch_versions = ch_versions.mix(BETCROP_ANTSBET.out.versions.first())

// ** Setting BET output ** //
image_bet = BETCROP_ANTSBET.out.t1
mask_bet = BETCROP_ANTSBET.out.mask
}

// ** crop image ** //
ch_crop = BETCROP_ANTSBET.out.t1.map{it + [[]]}
ch_crop = image_bet.t1.map{it + [[]]}
BETCROP_CROPVOLUME_T1 ( ch_crop )
ch_versions = ch_versions.mix(BETCROP_CROPVOLUME_T1.out.versions.first())

// ** crop mask ** //
ch_crop_mask = BETCROP_ANTSBET.out.mask.join(BETCROP_CROPVOLUME_T1.out.bounding_box)
ch_crop_mask = mask_bet.mask.join(BETCROP_CROPVOLUME_T1.out.bounding_box)
BETCROP_CROPVOLUME_MASK ( ch_crop_mask )
ch_versions = ch_versions.mix(BETCROP_CROPVOLUME_MASK.out.versions.first())

emit:
image_nlmeans = DENOISING_NLMEANS.out.image // channel: [ val(meta), [ image ] ]
image_N4 = PREPROC_N4.out.image // channel: [ val(meta), [ image ] ]
image_resample = IMAGE_RESAMPLE.out.image // channel: [ val(meta), [ image ] ]
image_bet = BETCROP_ANTSBET.out.t1 // channel: [ val(meta), [ t1 ] ]
mask_bet = BETCROP_ANTSBET.out.mask // channel: [ val(meta), [ mask ] ]
image_nlmeans = DENOISING_NLMEANS.out.image // channel: [ val(meta), [ image ] ]
image_N4 = PREPROC_N4.out.image // channel: [ val(meta), [ image ] ]
image_resample = IMAGE_RESAMPLE.out.image // channel: [ val(meta), [ image ] ]
image_bet = image_bet // channel: [ val(meta), [ t1 ] ]
mask_bet = mask_bet // channel: [ val(meta), [ mask ] ]
crop_box = BETCROP_CROPVOLUME_T1.out.bounding_box // channel: [ val(meta), [ bounding_box ] ]
mask_final = BETCROP_CROPVOLUME_MASK.out.image // channel: [ val(meta), [ mask ] ]
mask_final = BETCROP_CROPVOLUME_MASK.out.image // channel: [ val(meta), [ mask ] ]
t1_final = BETCROP_CROPVOLUME_T1.out.image // channel: [ val(meta), [ image ] ]
versions = ch_versions // channel: [ versions.yml ]
versions = ch_versions // channel: [ versions.yml ]
}
9 changes: 8 additions & 1 deletion subworkflows/nf-neuro/preproc_t1/meta.yml
View file
Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ description: |
Resamples the T1 to an isotropic spatial resolution. The default is 1mm, a standard in humans which
usually facilitate registration with corrected DWI images.
This spatial resolution is modifiable in the configuration file.
Brain Extraction (bet, ANTs).
Brain Extraction (bet, ANTs, freesurfer).
Isolates the brain tissue voxels from the remaining image. Also creates a binary brain mask.
This brain extraction is required for the T1 to DWI Registration.
Cropping (scil).
Expand All @@ -42,6 +42,7 @@ components:
- preproc/n4
- image/resample
- betcrop/antsbet
- betcrop/synthbet
- betcrop/cropvolume

input:
Expand Down Expand Up @@ -81,6 +82,12 @@ input:
The input channel containing the reference for the resampling. Optional
Structure: [ val(meta), path(ref) ]
pattern: "*.{nii,nii.gz}"
- ch_weights:
type: file
description: |
The input channel containing an alternative model weights for synthbet. Optional
Structure: [ val(meta), path (weights)]
pattern: "*.pt"
output:
- image_nlmeans:
type: file
Expand Down
104 changes: 102 additions & 2 deletions subworkflows/nf-neuro/preproc_t1/tests/main.nf.test
View file
Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@ nextflow_workflow {
tag "preproc/n4"
tag "image/resample"
tag "betcrop/antsbet"
tag "becrop/synthbet"
tag "betcrop/cropvolume"

tag "load_test_data"
Expand Down Expand Up @@ -69,14 +70,29 @@ nextflow_workflow {
[ id:'test', single_end:false ],
[]
]}
input[6] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[]
]}
"""
}
}

then {
assertAll(
{ assert workflow.success},
{ assert snapshot(workflow.out).match()}
{ assert snapshot(
niftiMD5SUM(workflow.out.image_nlmeans.get(0).get(1)),
niftiMD5SUM(workflow.out.image_N4.get(0).get(1)),
niftiMD5SUM(workflow.out.image_resample.get(0).get(1)),
niftiMD5SUM(workflow.out.image_bet.get(0).get(1)),
niftiMD5SUM(workflow.out.mask_bet.get(0).get(1)),
workflow.out.crop_box,
niftiMD5SUM(workflow.out.mask_final.get(0).get(1)),
niftiMD5SUM(workflow.out.t1_final.get(0).get(1)),
workflow.out.versions
).match()}
)
}
}
Expand Down Expand Up @@ -123,14 +139,98 @@ nextflow_workflow {
[ id:'test', single_end:false ],
file("\${test_data_directory}/t1_unaligned.nii.gz")
]}
input[6] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[]
]}
"""
}
}

then {
assertAll(
{ assert workflow.success},
{ assert snapshot(
niftiMD5SUM(workflow.out.image_nlmeans.get(0).get(1)),
niftiMD5SUM(workflow.out.image_N4.get(0).get(1)),
niftiMD5SUM(workflow.out.image_resample.get(0).get(1)),
niftiMD5SUM(workflow.out.image_bet.get(0).get(1)),
niftiMD5SUM(workflow.out.mask_bet.get(0).get(1)),
workflow.out.crop_box,
niftiMD5SUM(workflow.out.mask_final.get(0).get(1)),
niftiMD5SUM(workflow.out.t1_final.get(0).get(1)),
workflow.out.versions
).match()}
)
}
}

test("preproc_t1_synthbet") {
config "./nextflow_synthbet.config"

when {
workflow {
"""
ch_split_test_data = LOAD_DATA.out.test_data_directory
.branch{
antsbet: it.simpleName == "antsbet"
others: it.simpleName == "others"
}
input[0] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
file("\${test_data_directory}/t1_unaligned.nii.gz")
]}
input[1] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[]
]}
input[2] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[]
]}
input[3] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[]
]}
input[4] = ch_split_test_data.others.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[],
[]
]}
input[5] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[]
]}
input[6] = ch_split_test_data.antsbet.map{
test_data_directory -> [
[ id:'test', single_end:false ],
[]
]}
"""
}
}

then {
assertAll(
{ assert workflow.success},
{ assert snapshot(workflow.out).match()}
{ assert snapshot(
niftiMD5SUM(workflow.out.image_nlmeans.get(0).get(1)),
niftiMD5SUM(workflow.out.image_N4.get(0).get(1)),
niftiMD5SUM(workflow.out.image_resample.get(0).get(1)),
niftiMD5SUM(workflow.out.image_bet.get(0).get(1)),
niftiMD5SUM(workflow.out.mask_bet.get(0).get(1)),
workflow.out.crop_box,
niftiMD5SUM(workflow.out.mask_final.get(0).get(1)),
niftiMD5SUM(workflow.out.t1_final.get(0).get(1)),
workflow.out.versions
).match()}
)
}
}
Expand Down

0 comments on commit eee93dc

Please sign in to comment.