.github/workflows/ci.yml

@@ -54,8 +54,8 @@ jobs:
           jq
       - name: Copy junifer-data directory
         run: |
-          mkdir -p $HOME/junifer_data/v4
-          cp -ar /root/junifer_data/v4/. $HOME/junifer_data/v4/
+          mkdir -p $HOME/junifer_data/v7
+          cp -ar /root/junifer_data/v7/. $HOME/junifer_data/v7/
       - name: Checkout repository
         uses: actions/checkout@v5
         with:

.github/workflows/docs-preview.yml

@@ -40,8 +40,8 @@ jobs:
         jq
     - name: Copy junifer-data directory
       run: |
-        mkdir -p $HOME/junifer_data/v4
-        cp -ar /root/junifer_data/v4/. $HOME/junifer_data/v4/
+        mkdir -p $HOME/junifer_data/v7
+        cp -ar /root/junifer_data/v7/. $HOME/junifer_data/v7/
     - name: Checkout repository
       uses: actions/checkout@v5
       with:

.github/workflows/docs.yml

@@ -31,8 +31,8 @@ jobs:
         jq
     - name: Copy junifer-data directory
       run: |
-        mkdir -p $HOME/junifer_data/v4
-        cp -ar /root/junifer_data/v4/. $HOME/junifer_data/v4/
+        mkdir -p $HOME/junifer_data/v7
+        cp -ar /root/junifer_data/v7/. $HOME/junifer_data/v7/
     - name: Checkout repository
       uses: actions/checkout@v5
       with:

docs/builtin.rst

@@ -463,6 +463,24 @@ Available
        | structures in the human brain.
        | Neuron., Volume 33(3), Pages 341-355 (2002).
        | https://doi:10.1016/s0896-6273(02)00569-x
+   * - Glasser
+     - None
+     - ``Glasser``
+     - ``MNI152NLin2009cAsym``
+     - 0.0.7
+     - | Glasser, M.F., Coalson, T.S., Robinson, E.C. et al.
+       | A multi-modal parcellation of human cerebral cortex.
+       | Nature (2016).
+       | http://doi.org/10.1038/nature18933
+   * - Julich-Brain
+     - ``version``
+     - ``Julich-Brain_V1_18``, ``Julich-Brain_V2_9``, ``Julich-Brain_V3_0_3``, ``Julich-Brain_V3_1``
+     - ``MNI152NLin2009cAsym``
+     - 0.0.7
+     - | Amunts, K. et al.
+       | Julich-Brain: A 3D probabilistic atlas of the human brain’s cytoarchitecture.
+       | Science, 369, 988-992 (2020)
+       | https://doi.org/10.1126/science.abb4588
 
 
 Planned
@@ -480,11 +498,6 @@ Planned
        | on MRI scans into gyral based regions of interest.
        | NeuroImage, Volume 31(3), Pages 968-980 (2006).
        | http://doi.org/10.1016/j.neuroimage.2006.01.021
-   * - Glasser
-     - | Glasser, M.F., Coalson, T.S., Robinson, E.C. et al.
-       | A multi-modal parcellation of human cerebral cortex.
-       | Nature (2016).
-       | http://doi.org/10.1038/nature18933
    * - AAL
      - | Rolls, E.T., Huang, C.C., Lin, C.P., et al.
        | Automated anatomical labelling atlas 3.

docs/changes/newsfragments/486.enh

@@ -0,0 +1 @@
+Add Glasser and Julich-Brain parcellations to :class:`.ParcellationRegistry` by `Synchon Mandal`_

docs/changes/newsfragments/486.misc

@@ -0,0 +1 @@
+Bump ``junifer-data`` to ``v7`` by `Synchon Mandal`_

junifer/data/parcellations/_parcellations.py

@@ -199,6 +199,26 @@ class ParcellationRegistry(BasePipelineDataRegistry):
                 }
             }
         )
+        # Add Glasser
+        self._builtin.update(
+            {
+                "Glasser": {
+                    "family": "Glasser",
+                    "space": "MNI152NLin2009cAsym",
+                }
+            }
+        )
+        # Add Julich-Brain
+        for v in ["V1_18", "V2_9", "V3_0_3", "V3_1"]:
+            self._builtin.update(
+                {
+                    f"Julich-Brain_{v}": {
+                        "family": "Julich-Brain",
+                        "version": v,
+                        "space": "MNI152NLin2009cAsym",
+                    }
+                }
+            )
 
         # Update registry with built-in ones
         self._registry.update(self._builtin)
@@ -365,6 +385,8 @@ class ParcellationRegistry(BasePipelineDataRegistry):
             "Yan2023",
             "Brainnetome",
             "FreeSurfer",
+            "Glasser",
+            "Julich-Brain",
         ]:
             # Load parcellation and labels
             if t_family == "Schaefer2018":
@@ -408,6 +430,17 @@ class ParcellationRegistry(BasePipelineDataRegistry):
                 parcellation_fname, parcellation_labels = _retrieve_aseg(
                     resolution=resolution,
                 )
+            elif t_family == "Glasser":
+                parcellation_fname, parcellation_labels = _retrieve_glasser(
+                    resolution=resolution,
+                )
+            elif t_family == "Julich-Brain":
+                parcellation_fname, parcellation_labels = (
+                    _retrieve_julich_brain(
+                        resolution=resolution,
+                        **parcellation_definition,
+                    )
+                )
         else:
             raise_error(f"Unknown parcellation family: {t_family}")
 
@@ -1421,6 +1454,111 @@ def _retrieve_aseg(
     return parcellation_img_path, labels
 
 
+def _retrieve_glasser(
+    resolution: Optional[float] = None,
+) -> tuple[Path, list[str]]:
+    """Retrieve Glasser v1.0 .
+
+    Parameters
+    ----------
+    resolution : 1.0, optional
+        The desired resolution of the parcellation to load. If it is not
+        available, the closest resolution will be loaded. Preferably, use a
+        resolution higher than the desired one. By default, will load the
+        highest one (default None). Available resolution for this
+        parcellation is 1mm.
+
+    Returns
+    -------
+    pathlib.Path
+        File path to the parcellation image.
+    list of str
+        Parcellation labels.
+
+    """
+    logger.info("Parcellation parameters:")
+    logger.info(f"\tresolution: {resolution}")
+
+    _valid_resolutions = [1.0]
+    _ = closest_resolution(resolution, _valid_resolutions)
+
+    path_prefix = Path("parcellations/Glasser/2021")
+    parcellation_img_path = get(
+        file_path=path_prefix / "MNI_Glasser_HCP_v1.0.nii.gz",
+        dataset_path=get_dataset_path(),
+        **JUNIFER_DATA_PARAMS,
+    )
+    parcellation_label_path = get(
+        file_path=path_prefix / "labels.csv",
+        dataset_path=get_dataset_path(),
+        **JUNIFER_DATA_PARAMS,
+    )
+    labels = pd.read_csv(parcellation_label_path, sep=",")["label"].to_list()
+
+    return parcellation_img_path, labels
+
+
+def _retrieve_julich_brain(
+    resolution: Optional[float] = None,
+    version: str = "v3_1",
+) -> tuple[Path, list[str]]:
+    """Retrieve Julich-Brain labelled parcellations.
+
+    Parameters
+    ----------
+    resolution : 1.0, optional
+        The desired resolution of the parcellation to load. If it is not
+        available, the closest resolution will be loaded. Preferably, use a
+        resolution higher than the desired one. By default, will load the
+        highest one (default None). Available resolution for this
+        parcellation is 1mm.
+    version : {"V1_18", "V2_9", "V3_0_3", "V3_1"}, optional
+        The version of the parcellation to use (default "V3_1").
+
+    Returns
+    -------
+    pathlib.Path
+        File path to the parcellation image.
+    list of str
+        Parcellation labels.
+
+    Raises
+    ------
+    ValueError
+        If invalid value is provided for ``version``.
+
+    """
+    logger.info("Parcellation parameters:")
+    logger.info(f"\tresolution: {resolution}")
+    logger.info(f"\tversion: {version}")
+
+    # Check version
+    _valid_version = ["V1_18", "V2_9", "V3_0_3", "V3_1"]
+    if version not in _valid_version:
+        raise_error(
+            f"The parameter `version` ({version}) needs to be one of the "
+            f"following: {_valid_version}"
+        )
+
+    _valid_resolutions = [1.0]
+    _ = closest_resolution(resolution, _valid_resolutions)
+
+    path_prefix = Path(f"parcellations/Julich-Brain/{version}")
+    parcellation_img_path = get(
+        file_path=path_prefix / "labelled.nii.gz",
+        dataset_path=get_dataset_path(),
+        **JUNIFER_DATA_PARAMS,
+    )
+    parcellation_label_path = get(
+        file_path=path_prefix / "labels.csv",
+        dataset_path=get_dataset_path(),
+        **JUNIFER_DATA_PARAMS,
+    )
+    labels = pd.read_csv(parcellation_label_path, sep=",")["label"].to_list()
+
+    return parcellation_img_path, labels
+
+
 def merge_parcellations(
     parcellations_list: list["Nifti1Image"],
     parcellations_names: list[str],

junifer/data/parcellations/tests/test_parcellations.py

@@ -23,6 +23,7 @@ from junifer.data.parcellations import merge_parcellations
 from junifer.data.parcellations._parcellations import (
     _retrieve_aicha,
     _retrieve_brainnetome,
+    _retrieve_julich_brain,
     _retrieve_schaefer,
     _retrieve_shen,
     _retrieve_suit,
@@ -962,6 +963,75 @@ def test_aseg() -> None:
     )
 
 
+def test_glasser() -> None:
+    """Test Glasser parcellation."""
+    parcellations = list_data(kind="parcellation")
+    assert "Glasser" in parcellations
+
+    # Load parcellation
+    img, label, img_path, space = load_data(
+        kind="parcellation",
+        name="Glasser",
+        target_space="MNI152NLin2009cAsym",
+    )
+    assert img is not None
+    assert img_path.name == "MNI_Glasser_HCP_v1.0.nii.gz"
+    assert space == "MNI152NLin2009cAsym"
+    assert len(label) == 360
+    assert_array_equal(
+        img.header["pixdim"][1:4],
+        3 * [1],
+    )
+
+
+@pytest.mark.parametrize(
+    "version, rois",
+    [
+        ("V1_18", 202),
+        ("V2_9", 294),
+        ("V3_0_3", 314),
+        ("V3_1", 414),
+    ],
+)
+def test_julich_brain(version: str, rois: int) -> None:
+    """Test Julich-Brain parcellation.
+
+    Parameters
+    ----------
+    version : str
+        The parametrized version.
+    rois : int
+        The parametrized # of ROIs.
+
+    """
+    parcellations = list_data(kind="parcellation")
+    n = f"Julich-Brain_{version}"
+    assert n in parcellations
+
+    # Load parcellation
+    img, label, img_path, space = load_data(
+        kind="parcellation",
+        name=n,
+        target_space="MNI152NLin2009cAsym",
+    )
+    assert img is not None
+    assert img_path.name == "labelled.nii.gz"
+    assert space == "MNI152NLin2009cAsym"
+    assert len(label) == rois
+    assert_array_equal(
+        img.header["pixdim"][1:4],
+        3 * [1],
+    )
+
+
+def test_retrieve_julich_brain_incorrect_version() -> None:
+    """Test retrieve Julich-Brain with incorrect version."""
+    with pytest.raises(ValueError, match=r"The parameter `version`"):
+        _retrieve_julich_brain(
+            version="v0",
+        )
+
+
 def test_merge_parcellations() -> None:
     """Test merging parcellations."""
     # load some parcellations for testing

junifer/data/utils.py

@@ -24,10 +24,10 @@ __all__ = [
 
 
 # junifer-data version constant
-JUNIFER_DATA_VERSION = "5"
+JUNIFER_DATA_VERSION = "7"
 
 # junifer-data hexsha constant
-JUNIFER_DATA_HEXSHA = "62a0e3d187259a3c3ba7be638ee39cfb40df0a61"
+JUNIFER_DATA_HEXSHA = "f5144e6fef7d6f4f26508c3653d94a622f10207c"
 
 JUNIFER_DATA_PARAMS = {
     "tag": JUNIFER_DATA_VERSION,