New module to burn voxels

modules/nf-neuro/image/burnvoxels/environment.yml

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+channels: []
+dependencies: []
+name: image_burnvoxels

modules/nf-neuro/image/burnvoxels/main.nf

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+process IMAGE_BURNVOXELS {
+    tag "$meta.id"
+    label 'process_single'
+
+    container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?
+        'https://scil.usherbrooke.ca/containers/scilus_2.0.2.sif':
+        'scilus/scilus:2.0.2' }"
+
+    input:
+    tuple val(meta), path(masks), path(anat)
+
+    output:
+    tuple val(meta), path("*__all.nii.gz"), emit: all_masks_burned
+    tuple val(meta), path("*__*_*.nii.gz"), emit: each_mask_burned
+    path "versions.yml"           , emit: versions
+
+    when:
+    task.ext.when == null || task.ext.when
+
+    script:
+    def args = task.ext.args ?: ''
+    def prefix = task.ext.prefix ?: "${meta.id}"
+    String masks_list = masks.join(", ").replace(',', '')
+    Integer nb_masks = masks.size()
+    """
+    # Normalize the anatomy between 0 and 300
+    scil_volume_math.py convert ${anat} anat_f32.nii.gz --data_type float32 -f
+    scil_volume_math.py normalize_max anat_f32.nii.gz anat_normalize.nii.gz -f
+    mrcalc 300 anat_normalize.nii.gz -multiply anat_normalize_300.nii.gz -force
+
+    # Set the step value for be applied to each bundle
+    mkdir masks_burned/
+    cnt=25
+    nb_masks=${nb_masks}
+    step=\$(echo 300 \${nb_masks} | awk '{print \$1 / (\$2 - 1)}')
+
+    for m in ${masks_list};
+    do
+        mname=\${m%%.*}
+        mname=\${mname##*__}
+        scil_volume_math.py convert \${m} masks_burned/tmp_\${mname}_f32.nii.gz --data_type float32 -f
+        mrcalc \${cnt} masks_burned/tmp_\${mname}_f32.nii.gz -multiply masks_burned/mask_\${mname}_\${cnt}.nii.gz -force
+        ImageMath 3 ${prefix}__\${mname}_\${cnt}.nii.gz addtozero masks_burned/mask_\${mname}_\${cnt}.nii.gz anat_normalize_300.nii.gz
+        rm masks_burned/tmp_\${mname}_f32.nii.gz
+        cnt=\$(echo \$cnt \${step} | awk '{print \$1 + \$2}');
+    done
+
+    echo $nb_masks
+    if [ \$nb_masks -eq 1 ]; then
+        mv masks_burned/mask_*.nii.gz mask_all_masks.nii.gz
+    else
+        scil_volume_math.py addition masks_burned/mask_*.nii.gz mask_all_masks.nii.gz -f
+    fi
+
+    ImageMath 3 ${prefix}__all.nii.gz addtozero mask_all_masks.nii.gz anat_normalize_300.nii.gz
+
+    cat <<-END_VERSIONS > versions.yml
+    "${task.process}":
+        ants: \$(antsRegistration --version | grep Version |  cut -d" " -f3)
+        mrtrix \$(mrcalc -version | grep mrcalc | cut -d" " -f3)
+        scilpy: \$(pip list --disable-pip-version-check --no-python-version-warning | grep scilpy | tr -s ' ' | cut -d' ' -f2)
+    END_VERSIONS
+    """
+
+    stub:
+    def args = task.ext.args ?: ''
+    def prefix = task.ext.prefix ?: "${meta.id}"
+    """
+    touch ${prefix}__all.nii.gz
+    touch ${prefix}__AF_L_25.nii.gz
+    touch ${prefix}__AF_L_125.nii.gz
+
+    cat <<-END_VERSIONS > versions.yml
+    "${task.process}":
+        ants: \$(antsRegistration --version | grep Version |  cut -d" " -f3)
+        mrtrix \$(mrcalc -version | grep mrcalc | cut -d" " -f3)
+        scilpy: \$(pip list --disable-pip-version-check --no-python-version-warning | grep scilpy | tr -s ' ' | cut -d' ' -f2)
+    END_VERSIONS
+    """
+}

modules/nf-neuro/image/burnvoxels/meta.yml

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+name: "image_burnvoxels"
+description: |
+  1. **Burning Voxels**: The module takes binary masks and "burns" or imprints their voxels onto an anatomical image.
+  This means that the areas defined by the masks are marked or labeled on the anatomical image.
+
+  2. **Output Images**: The module generates multiple output images:
+    - One image with all masks burned onto the anatomical image.
+    - Separate images for each mask burned onto the anatomical image. If there are N masks, there will be N images.
+
+  3. **Label Values**: The burned voxels are assigned label values:
+    - The minimum label value is 25.
+    - Subsequent label values are incremented by a dynamically determined step based on the number of masks.
+
+  In summary, this module processes an anatomical image by applying binary masks to it, generating multiple labeled images as output.
+keywords:
+  - Image Processing
+  - Voxel Burning
+  - Mask Application
+tools:
+  - "ANTs":
+      description: "Advanced Normalization Tools (ANTs) for image processing."
+      homepage: "http://stnava.github.io/ANTs/"
+  - "mrtrix":
+      description: "MRtrix3 is a software package for various types of diffusion imaging data, including diffusion-weighted, diffusion-tensor, and q-ball imaging."
+      homepage: "https://www.mrtrix.org/"
+  - "scilpy":
+      description: "The Sherbrooke Connectivity Imaging Lab (SCIL) Python dMRI processing toolbox."
+      homepage: "https://github.com/scilus/scilpy.git"
+
+input:
+  - meta:
+      type: map
+      description: |
+        Groovy Map containing sample information
+        e.g. `[ id:'sample1', single_end:false ]`
+
+  - masks:
+      type: list
+      description: List of binary masks to be burned onto the anatomical image.
+      pattern: "*.nii.gz"
+
+  - anat:
+      type: file
+      description: Anatomical image to burn the masks onto.
+      pattern: "*.nii.gz"
+
+output:
+  - meta:
+      type: map
+      description: |
+        Groovy Map containing sample information
+        e.g. `[ id:'sample1', single_end:false ]`
+
+  - all_masks_burned:
+      type: file
+      description: Anatomical image with all masks burned onto it.
+      pattern: "*.nii.gz"
+
+  - each_mask_burned:
+      type: list
+      description: Anatomical image with each mask burned onto it.
+      pattern: "*.nii.gz"
+
+  - versions:
+      type: file
+      description: File containing software versions
+      pattern: "versions.yml"
+
+authors:
+  - "@GuillaumeTh"
+maintainers:
+  - "@GuillaumeTh"

modules/nf-neuro/image/burnvoxels/tests/main.nf.test

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+nextflow_process {
+
+    name "Test Process IMAGE_BURNVOXELS"
+    script "../main.nf"
+    process "IMAGE_BURNVOXELS"
+
+    tag "modules"
+    tag "modules_nfcore"
+    tag "image"
+    tag "image/burnvoxels"
+
+    tag "subworkflows"
+    tag "subworkflows/load_test_data"
+
+    setup {
+        run("LOAD_TEST_DATA", alias: "LOAD_DATA") {
+            script "../../../../../subworkflows/nf-neuro/load_test_data/main.nf"
+            process {
+                """
+                input[0] = Channel.from( [ "tractometry.zip" ] )
+                input[1] = "test.load-test-data"
+                """
+            }
+        }
+    }
+
+    test("burnvoxels - two masks") {
+
+        when {
+            process {
+                """
+                input[0] = LOAD_DATA.out.test_data_directory.map{
+                    test_data_directory -> [
+                        [ id:'test', single_end:false ], // meta map
+                        [file("\${test_data_directory}/IFGWM.nii.gz"), file("\${test_data_directory}/IFGWM_labels_map.nii.gz")],
+                        file("\${test_data_directory}/mni_masked.nii.gz")
+                    ]
+                }
+                """
+            }
+        }
+
+        then {
+            assertAll(
+                { assert process.success },
+                { assert snapshot(process.out).match() }
+            )
+        }
+    }
+}

modules/nf-neuro/image/burnvoxels/tests/main.nf.test.snap

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+{
+    "burnvoxels - two masks": {
+        "content": [
+            {
+                "0": [
+                    [
+                        {
+                            "id": "test",
+                            "single_end": false
+                        },
+                        "test__all.nii.gz:md5,7e8fe36daf0dfba28a5701c55e98a0ab"
+                    ]
+                ],
+                "1": [
+                    [
+                        {
+                            "id": "test",
+                            "single_end": false
+                        },
+                        [
+                            "test__IFGWM_25.nii.gz:md5,d9654356d7f9c2b0eda5f69e8e71b9c4",
+                            "test__IFGWM_labels_map_325.nii.gz:md5,1169f8f2dba2ef2addaea6afd0ee82c2"
+                        ]
+                    ]
+                ],
+                "2": [
+                    "versions.yml:md5,950062f43518f49bd79589bb79b16191"
+                ],
+                "all_masks_burned": [
+                    [
+                        {
+                            "id": "test",
+                            "single_end": false
+                        },
+                        "test__all.nii.gz:md5,7e8fe36daf0dfba28a5701c55e98a0ab"
+                    ]
+                ],
+                "each_mask_burned": [
+                    [
+                        {
+                            "id": "test",
+                            "single_end": false
+                        },
+                        [
+                            "test__IFGWM_25.nii.gz:md5,d9654356d7f9c2b0eda5f69e8e71b9c4",
+                            "test__IFGWM_labels_map_325.nii.gz:md5,1169f8f2dba2ef2addaea6afd0ee82c2"
+                        ]
+                    ]
+                ],
+                "versions": [
+                    "versions.yml:md5,950062f43518f49bd79589bb79b16191"
+                ]
+            }
+        ],
+        "meta": {
+            "nf-test": "0.9.0",
+            "nextflow": "24.10.0"
+        },
+        "timestamp": "2024-10-30T15:22:58.330309703"
+    }
+}

modules/nf-neuro/image/burnvoxels/tests/tags.yml

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+image/burnvoxels:
+  - "modules/nf-neuro/image/burnvoxels/**"