docs/changes/latest.inc

@@ -40,6 +40,9 @@ Enhancements
 - Add support for nilearn computed masks (``compute_epi_mask``, ``compute_brain_mask``, ``compute_background_mask``,
   ``fetch_icbm152_brain_gm_mask``) (:gh:`175` by `Fede Raimondo`_).
 
+- Add fMRIPrep brain masks to the datagrabber patterns for all datagrabbers in the aomic sub-package
+  (:gh:`177` by `Leonard Sasse`_).
+
 Bugs
 ~~~~
 

junifer/datagrabber/aomic/id1000.py

@@ -7,7 +7,7 @@
 # License: AGPL
 
 from pathlib import Path
-from typing import Union
+from typing import Union, Dict
 
 from junifer.datagrabber import PatternDataladDataGrabber
 
@@ -34,7 +34,9 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
         types = [
             "BOLD",
             "BOLD_confounds",
+            "BOLD_mask",
             "T1w",
+            "T1w_mask",
             "probseg_CSF",
             "probseg_GM",
             "probseg_WM",
@@ -52,11 +54,22 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
                 "sub-{subject}_task-moviewatching_"
                 "desc-confounds_regressors.tsv"
             ),
+            "BOLD_mask": (
+                "derivatives/fmriprep/sub-{subject}/func/"
+                "sub-{subject}_task-moviewatching_"
+                "space-MNI152NLin2009cAsym_"
+                "desc-brain_mask.nii.gz"
+            ),
             "T1w": (
                 "derivatives/fmriprep/sub-{subject}/anat/"
                 "sub-{subject}_space-MNI152NLin2009cAsym_"
                 "desc-preproc_T1w.nii.gz"
             ),
+            "T1w_mask": (
+                "derivatives/fmriprep/sub-{subject}/anat/"
+                "sub-{subject}_space-MNI152NLin2009cAsym_"
+                "desc-brain_mask.nii.gz"
+            ),
             "probseg_CSF": (
                 "derivatives/fmriprep/sub-{subject}/anat/"
                 "sub-{subject}_space-MNI152NLin2009cAsym_label-"
@@ -88,3 +101,22 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
             replacements=replacements,
             confounds_format="fmriprep",
         )
+
+    def get_item(self, subject: str) -> Dict:
+        """Index one element in the dataset.
+
+        Parameters
+        ----------
+        subject : str
+            The subject ID.
+
+        Returns
+        -------
+        out : dict
+            Dictionary of paths for each type of data required for the
+            specified element.
+        """
+        out = super().get_item(subject=subject)
+        out["BOLD"]["mask_item"] = "BOLD_mask"
+        out["T1w"]["mask_item"] = "T1w_mask"
+        return out

junifer/datagrabber/aomic/piop1.py

@@ -41,7 +41,9 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
         types = [
             "BOLD",
             "BOLD_confounds",
+            "BOLD_mask",
             "T1w",
+            "T1w_mask",
             "probseg_CSF",
             "probseg_GM",
             "probseg_WM",
@@ -83,11 +85,21 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
                 "sub-{subject}_task-{task}_"
                 "desc-confounds_regressors.tsv"
             ),
+            "BOLD_mask": (
+                "derivatives/fmriprep/sub-{subject}/func/"
+                "sub-{subject}_task-{task}_"
+                "space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz"
+            ),
             "T1w": (
                 "derivatives/fmriprep/sub-{subject}/anat/"
                 "sub-{subject}_space-MNI152NLin2009cAsym_"
                 "desc-preproc_T1w.nii.gz"
             ),
+            "T1w_mask": (
+                "derivatives/fmriprep/sub-{subject}/anat/"
+                "sub-{subject}_space-MNI152NLin2009cAsym_"
+                "desc-brain_mask.nii.gz"
+            ),
             "probseg_CSF": (
                 "derivatives/fmriprep/sub-{subject}/anat/"
                 "sub-{subject}_space-MNI152NLin2009cAsym_label-"
@@ -149,6 +161,8 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
         new_task = f"{task}_acq-{acq}"
 
         out = super().get_item(subject=subject, task=new_task)
+        out["BOLD"]["mask_item"] = "BOLD_mask"
+        out["T1w"]["mask_item"] = "T1w_mask"
         return out
 
     def get_elements(self) -> List:

junifer/datagrabber/aomic/piop2.py

@@ -7,7 +7,7 @@
 # License: AGPL
 
 from pathlib import Path
-from typing import List, Union
+from typing import List, Union, Dict
 
 from junifer.datagrabber import PatternDataladDataGrabber
 
@@ -40,7 +40,9 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
         types = [
             "BOLD",
             "BOLD_confounds",
+            "BOLD_mask",
             "T1w",
+            "T1w_mask",
             "probseg_CSF",
             "probseg_GM",
             "probseg_WM",
@@ -80,11 +82,21 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
                 "sub-{subject}_task-{task}_acq-seq_"
                 "desc-confounds_regressors.tsv"
             ),
+            "BOLD_mask": (
+                "derivatives/fmriprep/sub-{subject}/func/"
+                "sub-{subject}_task-{task}_acq-seq_space"
+                "-MNI152NLin2009cAsym_desc-brain_mask.nii.gz"
+            ),
             "T1w": (
                 "derivatives/fmriprep/sub-{subject}/anat/"
                 "sub-{subject}_space-MNI152NLin2009cAsym_"
                 "desc-preproc_T1w.nii.gz"
             ),
+            "T1w_mask": (
+                "derivatives/fmriprep/sub-{subject}/anat/"
+                "sub-{subject}_space-MNI152NLin2009cAsym_"
+                "desc-brain_mask.nii.gz"
+            ),
             "probseg_CSF": (
                 "derivatives/fmriprep/sub-{subject}/anat/"
                 "sub-{subject}_space-MNI152NLin2009cAsym_label-"
@@ -127,3 +139,25 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
         """
         all_elements = super().get_elements()
         return [x for x in all_elements if x[1] in self.tasks]
+
+    def get_item(self, subject: str, task: str) -> Dict:
+        """Index one element in the dataset.
+
+        Parameters
+        ----------
+        subject : str
+            The subject ID.
+        task : str
+            The task to get. Possible values are:
+            {"restingstate", "stopsignal", "emomatching", "workingmemory"}
+
+        Returns
+        -------
+        out : dict
+            Dictionary of paths for each type of data required for the
+            specified element.
+        """
+        out = super().get_item(subject=subject, task=task)
+        out["BOLD"]["mask_item"] = "BOLD_mask"
+        out["T1w"]["mask_item"] = "T1w_mask"
+        return out

junifer/datagrabber/aomic/tests/test_id1000.py

@@ -51,6 +51,9 @@ def test_aomic1000_datagrabber() -> None:
         assert out["BOLD_confounds"]["path"].exists()
         assert out["BOLD_confounds"]["path"].is_file()
 
+        # assert BOLD_mask
+        assert out["BOLD_mask"]["path"].exists()
+
         # asserts type "T1w"
         assert "T1w" in out
 
@@ -63,6 +66,9 @@ def test_aomic1000_datagrabber() -> None:
         assert out["T1w"]["path"].exists()
         assert out["T1w"]["path"].is_file()
 
+        # asserts T1w_mask
+        assert out["T1w_mask"]["path"].exists()
+
         # asserts type "probseg_CSF"
         assert "probseg_CSF" in out
 

junifer/datagrabber/aomic/tests/test_piop1.py

@@ -66,6 +66,9 @@ def test_aomic_piop1_datagrabber() -> None:
             assert out["BOLD_confounds"]["path"].exists()
             assert out["BOLD_confounds"]["path"].is_file()
 
+            # assert BOLD_mask
+            assert out["BOLD_mask"]["path"].exists()
+
             # asserts type "T1w"
             assert "T1w" in out
 
@@ -78,6 +81,9 @@ def test_aomic_piop1_datagrabber() -> None:
             assert out["T1w"]["path"].exists()
             assert out["T1w"]["path"].is_file()
 
+            # asserts T1w_mask
+            assert out["T1w_mask"]["path"].exists()
+
             # asserts type "probseg_CSF"
             assert "probseg_CSF" in out
 

junifer/datagrabber/aomic/tests/test_piop2.py

@@ -35,7 +35,6 @@ def test_aomic_piop2_datagrabber() -> None:
 
             test_element = all_elements[0]
             sub, task = test_element
-
             out = dg[test_element]
 
             # asserts type "BOLD"
@@ -62,6 +61,9 @@ def test_aomic_piop2_datagrabber() -> None:
             assert out["BOLD_confounds"]["path"].exists()
             assert out["BOLD_confounds"]["path"].is_file()
 
+            # assert BOLD_mask
+            assert out["BOLD_mask"]["path"].exists()
+
             # asserts type "T1w"
             assert "T1w" in out
 
@@ -74,6 +76,9 @@ def test_aomic_piop2_datagrabber() -> None:
             assert out["T1w"]["path"].exists()
             assert out["T1w"]["path"].is_file()
 
+            # asserts T1w_mask
+            assert out["T1w_mask"]["path"].exists()
+
             # asserts type "probseg_CSF"
             assert "probseg_CSF" in out
 

tools/create_aomic1000_example_dataset.py

@@ -1,3 +1,5 @@
+"""Create a testing dataset for the DataladAOMICID1000 pattern datagrabber."""
+
 # Authors: Federico Raimondo <f.raimondo@fz-juelich.de>
 #          Vera Komeyer <v.komeyer@fz-juelich.de>
 #          Xuan Li <xu.li@fz-juelich.de>
@@ -8,7 +10,7 @@ from pathlib import Path
 import datalad.api as dl
 
 # repo has to be created on gin manually beforehand if not owner
-dst = 'git@gin.g-node.org:/juaml/datalad-example-aomic1000.git'
+dst = "git@gin.g-node.org:/juaml/datalad-example-aomic1000.git"
 
 # Use this if you create repo directly when pushing (see below)
 # dst_api = 'git@gin.g-node.org'
@@ -19,57 +21,81 @@ with TemporaryDirectory() as tmpdir_name:
     tmpdir = Path(tmpdir_name)
     ds = dl.create(tmpdir)  # type: ignore
 
-    base_dir = tmpdir / 'derivatives'
+    base_dir = tmpdir / "derivatives"
     base_dir.mkdir(exist_ok=True, parents=True)
 
-    for dtype in ['dwipreproc', 'fmriprep']:
+    for dtype in ["dwipreproc", "fmriprep"]:
         dtype_dir = base_dir / dtype
         dtype_dir.mkdir()
 
         for i_sub in range(1, 10):
-            t_sub = f'sub-{i_sub:04d}'
+            t_sub = f"sub-{i_sub:04d}"
             sub_dir = dtype_dir / t_sub
             sub_dir.mkdir()
 
-            if dtype == 'fmriprep':
+            if dtype == "fmriprep":
-                for dname in ['func', 'anat']:
+                for dname in ["func", "anat"]:
                     (sub_dir / dname).mkdir()
 
                 fnames = [
-                    (f'anat/{t_sub}_space-MNI152NLin2009cAsym_desc-preproc'
+                    (
-                     '_T1w.nii.gz'),
+                        f"anat/{t_sub}_space-MNI152NLin2009cAsym_desc-preproc"
-                    (f'anat/{t_sub}_space-MNI152NLin2009cAsym_label-'
+                        "_T1w.nii.gz"
-                     'CSF_probseg.nii.gz'),
+                    ),
-                    (f'anat/{t_sub}_space-MNI152NLin2009cAsym_label-'
+                    (
-                     'GM_probseg.nii.gz'),
+                        f"anat/{t_sub}_space-MNI152NLin2009cAsym_label-"
-                    (f'anat/{t_sub}_space-MNI152NLin2009cAsym_label-'
+                        "CSF_probseg.nii.gz"
-                     'WM_probseg.nii.gz'),
+                    ),
-                    (f'func/{t_sub}_task-moviewatching_space-'
+                    (
-                     'MNI152NLin2009cAsym_desc-preproc_bold.nii.gz'),
+                        f"anat/{t_sub}_space-MNI152NLin2009cAsym_label-"
-                    (f'func/{t_sub}_task-moviewatching_space-'
+                        "GM_probseg.nii.gz"
-                     'MNI152NLin2009cAsym_desc-preproc_bold.json'),
+                    ),
-                    (f'func/{t_sub}_task-moviewatching_desc-confounds'
+                    (
-                     '_regressors.tsv'),
+                        f"anat/{t_sub}_space-MNI152NLin2009cAsym_label-"
-                    (f'func/{t_sub}_task-moviewatching_desc-confounds'
+                        "WM_probseg.nii.gz"
-                     '_regressors.json'),
+                    ),
+                    (
+                        f"func/{t_sub}_task-moviewatching_space-"
+                        "MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
+                    ),
+                    (
+                        f"func/{t_sub}_task-moviewatching_space-"
+                        "MNI152NLin2009cAsym_desc-preproc_bold.json"
+                    ),
+                    (
+                        f"func/{t_sub}_task-moviewatching_desc-confounds"
+                        "_regressors.tsv"
+                    ),
+                    (
+                        f"func/{t_sub}_task-moviewatching_desc-confounds"
+                        "_regressors.json"
+                    ),
+                    (
+                        f"func/{t_sub}_task-moviewatching_"
+                        "space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz"
+                    ),
+                    (
+                        f"anat/{t_sub}_space-MNI152NLin2009cAsym_"
+                        "desc-brain_mask.nii.gz"
+                    ),
                 ]
 
-            elif dtype == 'dwipreproc':
+            elif dtype == "dwipreproc":
-                dname = 'dwi'
+                dname = "dwi"
                 (sub_dir / dname).mkdir()
 
                 fnames = [
-                    (f'{dname}/{t_sub}_desc-preproc_dwi.nii.gz'),
+                    (f"{dname}/{t_sub}_desc-preproc_dwi.nii.gz"),
                 ]
 
             for fname in fnames:
-                with open(sub_dir / fname, 'w') as f:
+                with open(sub_dir / fname, "w") as f:
-                    f.write('placeholder')
+                    f.write("placeholder")
 
     ds.save(recursive=True)
     # use this to create the repo automatically, only possible for juaml owner
     # ds.create_sibling_gin(
     #   (org_name/repo_basename).as_posix(), name='gin', existing='reconfigure',
     #   api=dst_api, access_protocol='ssh')
-    ds.siblings('add', name='gin', url=dst)
+    ds.siblings("add", name="gin", url=dst)
-    ds.push(to='gin', force='all')
+    ds.push(to="gin", force="all")

tools/create_aomicpiop1_example_dataset.py

@@ -38,6 +38,10 @@ with TemporaryDirectory() as tmpdir_name:
                         f"anat/{t_sub}_space-MNI152NLin2009cAsym_desc-preproc"
                         "_T1w.nii.gz"
                     ),
+                    (
+                        f"anat/{t_sub}_space-MNI152NLin2009cAsym_"
+                        "desc-brain_mask.nii.gz"  
+                    ),
                     (
                         f"anat/{t_sub}_space-MNI152NLin2009cAsym_label-"
                         "CSF_probseg.nii.gz"
@@ -62,28 +66,24 @@ with TemporaryDirectory() as tmpdir_name:
                 ]
                 for t in tasks:
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_space-"
-                            f"func/{t_sub}_task-{t}_space-"
+                        "MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
-                            "MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
-                        )
                     )
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_space-"
-                            f"func/{t_sub}_task-{t}_space-"
+                        "MNI152NLin2009cAsym_desc-preproc_bold.json"
-                            "MNI152NLin2009cAsym_desc-preproc_bold.json"
-                        )
                     )
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_space-"
-                            f"func/{t_sub}_task-{t}_desc-confounds"
+                        "MNI152NLin2009cAsym_desc-brain_mask.nii.gz"
-                            "_regressors.tsv"
-                        )
                     )
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_desc-confounds"
-                            f"func/{t_sub}_task-{t}_desc-confounds"
+                        "_regressors.tsv"
-                            "_regressors.json"
+                    )
-                        )
+                    fnames.append(
+                        f"func/{t_sub}_task-{t}_desc-confounds"
+                        "_regressors.json"
                     )
 
             elif dtype == "dwipreproc":

tools/create_aomicpiop2_example_dataset.py

@@ -38,6 +38,10 @@ with TemporaryDirectory() as tmpdir_name:
                         f"anat/{t_sub}_space-MNI152NLin2009cAsym_desc-preproc"
                         "_T1w.nii.gz"
                     ),
+                    (
+                        f"anat/{t_sub}_space-MNI152NLin2009cAsym"
+                        "_desc-brain_mask.nii.gz"
+                    ),
                     (
                         f"anat/{t_sub}_space-MNI152NLin2009cAsym_label-"
                         "CSF_probseg.nii.gz"
@@ -60,28 +64,24 @@ with TemporaryDirectory() as tmpdir_name:
                 ]
                 for t in tasks:
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_space-"
-                            f"func/{t_sub}_task-{t}_space-"
+                        "MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
-                            "MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
-                        )
                     )
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_space-"
-                            f"func/{t_sub}_task-{t}_space-"
+                        "MNI152NLin2009cAsym_desc-preproc_bold.json"
-                            "MNI152NLin2009cAsym_desc-preproc_bold.json"
-                        )
                     )
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_space-"
-                            f"func/{t_sub}_task-{t}_desc-confounds"
+                        "MNI152NLin2009cAsym_desc-brain_mask.nii.gz"
-                            "_regressors.tsv"
-                        )
                     )
                     fnames.append(
-                        (
+                        f"func/{t_sub}_task-{t}_desc-confounds"
-                            f"func/{t_sub}_task-{t}_desc-confounds"
+                        "_regressors.tsv"
-                            "_regressors.json"
+                    )
-                        )
+                    fnames.append(
+                        f"func/{t_sub}_task-{t}_desc-confounds"
+                        "_regressors.json"
                     )
 
             elif dtype == "dwipreproc":