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#56 - make all preproc_t1 modules optional #73

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#56 - make all preproc_t1 modules optional #73

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dfc965c
make all preproc_t1 modules optional
ThoumyreStanislas Dec 12, 2024
dac62a8
Merge branch 'main' of github.com:scilus/nf-neuro into preproc_t1_option
ThoumyreStanislas Dec 20, 2024
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209 changes: 123 additions & 86 deletions subworkflows/nf-neuro/preproc_t1/main.nf
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Original file line number Diff line number Diff line change
Expand Up @@ -24,104 +24,141 @@ workflow PREPROC_T1 {

ch_versions = Channel.empty()

// ** Denoising ** //
// Result : [ meta, image, mask | [] ]
// Steps :
// - join [ meta, image, mask | null ]
// - map [ meta, image, mask | [] ]
ch_nlmeans = ch_image
.join(ch_mask_nlmeans, remainder: true)
.map{ it[0..1] + [it[2] ?: []] }

DENOISING_NLMEANS ( ch_nlmeans )
ch_versions = ch_versions.mix(DENOISING_NLMEANS.out.versions.first())

// ** N4 correction ** //
// Result : [ meta, image, reference | [], mask | [] ]
// Steps :
// - join [ meta, image ] + [ reference, mask ] | [ reference, null ] | [ null ]
// - map [ meta, image, reference | [], mask | [] ]
// - join [ meta, image, reference | [], mask | [], nlmeans-mask | null ]
// - map [ meta, image, reference | [], mask | [] ]
ch_N4 = DENOISING_NLMEANS.out.image
.join(ch_ref_n4, remainder: true)
.map{ it[0..1] + [it[2] ?: [], it[3] ?: []] }
.join(ch_mask_nlmeans, remainder: true)
.map{ it[0..2] + [it[3] ?: it[4] ?: []] }

PREPROC_N4 ( ch_N4 )
ch_versions = ch_versions.mix(PREPROC_N4.out.versions.first())

// ** Resampling ** //
// Result : [ meta, image, reference | [] ]
// Steps :
// - join [ meta, image, reference | null ]
// - map [ meta, image, reference | [] ]
ch_resampling = PREPROC_N4.out.image
.join(ch_ref_resample, remainder: true)
.map{ it[0..1] + [it[2] ?: []] }

IMAGE_RESAMPLE ( ch_resampling )
ch_versions = ch_versions.mix(IMAGE_RESAMPLE.out.versions.first())

// ** Brain extraction ** //
if ( params.run_synthbet ) {
// ** SYNTHBET ** //
// Result : [ meta, image, weights | [] ]
if ( params.run_denoising ) {

// ** Denoising ** //
// Result : [ meta, image, mask | [] ]
// Steps :
// - join [ meta, image, weights | null ]
// - map [ meta, image, weights | [] ]
ch_bet = IMAGE_RESAMPLE.out.image
.join(ch_weights, remainder: true)
// - join [ meta, image, mask | null ]
// - map [ meta, image, mask | [] ]
ch_nlmeans = ch_image
.join(ch_mask_nlmeans, remainder: true)
.map{ it[0..1] + [it[2] ?: []] }

BETCROP_SYNTHBET ( ch_bet )
ch_versions = ch_versions.mix(BETCROP_SYNTHBET.out.versions.first())
DENOISING_NLMEANS ( ch_nlmeans )
ch_versions = ch_versions.mix(DENOISING_NLMEANS.out.versions.first())
image_nlmeans = DENOISING_NLMEANS.out.image
}

else {
image_nlmeans = ch_image
}

// ** Setting BET output ** //
image_bet = BETCROP_SYNTHBET.out.bet_image
mask_bet = BETCROP_SYNTHBET.out.brain_mask
if ( params.run_N4 ) {
// ** N4 correction ** //
// Result : [ meta, image, reference | [], mask | [] ]
// Steps :
// - join [ meta, image ] + [ reference, mask ] | [ reference, null ] | [ null ]
// - map [ meta, image, reference | [], mask | [] ]
// - join [ meta, image, reference | [], mask | [], nlmeans-mask | null ]
// - map [ meta, image, reference | [], mask | [] ]
ch_N4 = image_nlmeans
.join(ch_ref_n4, remainder: true)
.map{ it[0..1] + [it[2] ?: [], it[3] ?: []] }
.join(ch_mask_nlmeans, remainder: true)
.map{ it[0..2] + [it[3] ?: it[4] ?: []] }

PREPROC_N4 ( ch_N4 )
ch_versions = ch_versions.mix(PREPROC_N4.out.versions.first())
image_N4 = PREPROC_N4.out.image
}

else {
image_N4 = image_nlmeans
}

if ( params.run_resampling ) {
// ** Resampling ** //
// Result : [ meta, image, reference | [] ]
// Steps :
// - join [ meta, image, reference | null ]
// - map [ meta, image, reference | [] ]
ch_resampling = image_N4
.join(ch_ref_resample, remainder: true)
.map{ it[0..1] + [it[2] ?: []] }

IMAGE_RESAMPLE ( ch_resampling )
ch_versions = ch_versions.mix(IMAGE_RESAMPLE.out.versions.first())
image_resample = IMAGE_RESAMPLE.out.image
}
else {
// ** ANTSBET ** //
// The template and probability maps are mandatory if running antsBET. Since the
// error message from nextflow when they are absent is either non-informative or
// missing, we use ifEmpty to provide a more informative one.
ch_bet = IMAGE_RESAMPLE.out.image
.join(ch_template.ifEmpty{ error("ANTS BET needs a template") })
.join(ch_probability_map.ifEmpty{ error("ANTS BET needs a tissue 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
image_resample = image_N4
}

// ** Crop image ** //
ch_crop = image_bet
.map{ it + [[]] }
if ( params.run_bet ) {
// ** Brain extraction ** //
if ( params.run_synthbet ) {
// ** SYNTHBET ** //
// Result : [ meta, image, weights | [] ]
// Steps :
// - join [ meta, image, weights | null ]
// - map [ meta, image, weights | [] ]
ch_bet = image_resample
.join(ch_weights, remainder: true)
.map{ it[0..1] + [it[2] ?: []] }

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 {
// ** ANTSBET ** //
// The template and probability maps are mandatory if running antsBET. Since the
// error message from nextflow when they are absent is either non-informative or
// missing, we use ifEmpty to provide a more informative one.
ch_bet = image_resample
.join(ch_template.ifEmpty{ error("ANTS BET needs a template") })
.join(ch_probability_map.ifEmpty{ error("ANTS BET needs a tissue 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
}
}
else{
image_bet = image_resample
mask_bet = Channel.empty()
}

if ( params.run_crop ) {
// ** Crop image ** //
ch_crop = image_bet
.map{ it + [[]] }

BETCROP_CROPVOLUME_T1 ( ch_crop )
ch_versions = ch_versions.mix(BETCROP_CROPVOLUME_T1.out.versions.first())
BETCROP_CROPVOLUME_T1 ( ch_crop )
ch_versions = ch_versions.mix(BETCROP_CROPVOLUME_T1.out.versions.first())
image_crop = BETCROP_CROPVOLUME_T1.out.image
bbox = BETCROP_CROPVOLUME_T1.out.bounding_box

// ** Crop mask ** //
ch_crop_mask = mask_bet
.join(BETCROP_CROPVOLUME_T1.out.bounding_box)
// ** Crop mask ** //
ch_crop_mask = mask_bet
.join(BETCROP_CROPVOLUME_T1.out.bounding_box)

BETCROP_CROPVOLUME_MASK ( ch_crop_mask )
ch_versions = ch_versions.mix(BETCROP_CROPVOLUME_MASK.out.versions.first())
BETCROP_CROPVOLUME_MASK ( ch_crop_mask )
ch_versions = ch_versions.mix(BETCROP_CROPVOLUME_MASK.out.versions.first())
mask_crop = BETCROP_CROPVOLUME_MASK.out.image
}
else{
image_crop = image_bet
mask_crop = []
bbox = []
}

emit:
t1_final = BETCROP_CROPVOLUME_T1.out.image // channel: [ val(meta), t1-preprocessed ]
mask_final = BETCROP_CROPVOLUME_MASK.out.image // channel: [ val(meta), t1-mask ]
image_nlmeans = DENOISING_NLMEANS.out.image // channel: [ val(meta), t1-after-denoise ]
image_N4 = PREPROC_N4.out.image // channel: [ val(meta), t1-after-unbias ]
image_resample = IMAGE_RESAMPLE.out.image // channel: [ val(meta), t1-after-resample ]
image_bet = image_bet // channel: [ val(meta), t1-after-bet ]
mask_bet = mask_bet // channel: [ val(meta), intermediary-mask ]
crop_box = BETCROP_CROPVOLUME_T1.out.bounding_box // channel: [ val(meta), bounding-box ]
versions = ch_versions // channel: [ versions.yml ]
t1_final = image_crop // channel: [ val(meta), t1-preprocessed ]
mask_final = mask_crop // channel: [ val(meta), t1-mask ]
image_nlmeans = image_nlmeans // channel: [ val(meta), t1-after-denoise ]
image_N4 = image_N4 // channel: [ val(meta), t1-after-unbias ]
image_resample = image_resample // channel: [ val(meta), t1-after-resample ]
image_bet = image_bet // channel: [ val(meta), t1-after-bet ]
mask_bet = mask_bet // channel: [ val(meta), intermediary-mask ]
crop_box = bbox // channel: [ val(meta), bounding-box ]
versions = ch_versions // channel: [ versions.yml ]
}
122 changes: 122 additions & 0 deletions subworkflows/nf-neuro/preproc_t1/tests/main.nf.test
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Original file line number Diff line number Diff line change
Expand Up @@ -216,4 +216,126 @@ nextflow_workflow {
)
}
}

test("preproc_t1_quick") {
config "./nextflow_quick.config"

when {
workflow {
"""
ch_split_test_data = LOAD_DATA.out.test_data_directory
.branch{
antsbet: it.simpleName == "antsbet"
t1w: it.simpleName == "T1w"
}
input[0] = ch_split_test_data.t1w.map{
test_data_directory -> [
[ id:'test', single_end:false ],
file("\${test_data_directory}/T1w.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.t1w.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() }
)
}
}

test("preproc_t1_quick_bis") {
config "./nextflow_quick_bis.config"

when {
workflow {
"""
ch_split_test_data = LOAD_DATA.out.test_data_directory
.branch{
antsbet: it.simpleName == "antsbet"
t1w: it.simpleName == "T1w"
}
input[0] = ch_split_test_data.t1w.map{
test_data_directory -> [
[ id:'test', single_end:false ],
file("\${test_data_directory}/T1w.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.t1w.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() }
)
}
}
}
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